suppressMessages(library(minfi))
suppressMessages(library(reshape))
suppressMessages(library(ggplot2))
suppressMessages(library(gridExtra))
suppressMessages(library(RColorBrewer))
suppressMessages(library(here))
suppressMessages(library(binom))
suppressMessages(library(limma))
options(stringsAsFactors = FALSE)
source(here("scripts","00_pretty_plots.R"))
suppressMessages(source(here("scripts","00_heat_scree_plot_generic.R")))
source(here("scripts","00_EM_array_uniform_background_maximise_betabinom.R"))
# wget https://www.ebi.ac.uk/arrayexpress/files/E-MTAB-4957/E-MTAB-4957.raw.1.zip
# wget https://www.ebi.ac.uk/arrayexpress/files/E-MTAB-4957/E-MTAB-4957.raw.2.zip
# wget https://www.ebi.ac.uk/arrayexpress/files/E-MTAB-4957/E-MTAB-4957.raw.3.zip
# wget https://www.ebi.ac.uk/arrayexpress/files/E-MTAB-4957/E-MTAB-4957.raw.4.zip
# wget https://www.ebi.ac.uk/arrayexpress/files/E-MTAB-4957/E-MTAB-4957.raw.5.zip
# unzip E-MTAB-4957.raw.1.zip
# unzip E-MTAB-4957.raw.2.zip
# unzip E-MTAB-4957.raw.3.zip
# unzip E-MTAB-4957.raw.4.zip
# unzip E-MTAB-4957.raw.5.zip
#wget https://www.ebi.ac.uk/arrayexpress/files/E-MTAB-4957/E-MTAB-4957.sdrf.txt
path<-"data/published_organoids/E_MTAB_4957"
sampleinfo_organoid <- read.table(here(path, "E-MTAB-4957.sdrf.txt"), header=T, sep="\t")
sampleinfo_organoid<-sampleinfo_organoid[,c(1:15,30:34,38:41)]
#sample info cleanup
sampleinfo_organoid$sentrix<-sapply(1:nrow(sampleinfo_organoid), function(x) strsplit(as.character(sampleinfo_organoid$Assay.Name)[x], "_")[[1]][1])
sampleinfo_organoid$array.id.path <- file.path(here(path), sampleinfo_organoid$Assay.Name)
rgset_organoid <- read.metharray(sampleinfo_organoid$array.id.path, verbose = FALSE)
# Background and dye bias correction with noob thhrough funnorm implemented in minfi
#http://bioconductor.org/help/course-materials/2015/BioC2015/methylation450k.html
MSet.illumina <- preprocessFunnorm(rgset_organoid)
## [preprocessFunnorm] Background and dye bias correction with noob
## Loading required package: IlluminaHumanMethylation450kmanifest
## Loading required package: IlluminaHumanMethylation450kanno.ilmn12.hg19
## [preprocessFunnorm] Mapping to genome
## [preprocessFunnorm] Quantile extraction
## [preprocessFunnorm] Normalization
MTAB_organoid_beta<-getBeta(MSet.illumina)
avg_detPval <- colMeans(detectionP(rgset_organoid))
sampleinfo_organoid$det_pval<-avg_detPval
print("detection pval")
## [1] "detection pval"
ggplot(sampleinfo_organoid)+geom_boxplot(aes(as.factor(sentrix), det_pval, fill=as.factor(sentrix)), outlier.shape = NA)+
geom_point(aes(as.factor(sentrix), det_pval, group=Assay.Name, fill=as.factor(sentrix)), shape=21, color="black",
position = position_jitter(w = 0.25))+theme_bw()+theme(axis.text.x=element_text(angle = 45, vjust = 1, hjust=1))+
xlab("Sentrix ID")+ylab("Mean Detection P Value")+guides(fill=FALSE)+ylim(0,0.008)
ggsave(here("figs","MTAB4957_detection_pvalue.pdf"), width=6, height=5)
ggsave(here("figs/jpeg","MTAB4957_detection_pvalue.jpeg"), width=6, height=5)
Beta distribution before and after normalization
beta_raw<-getBeta(rgset_organoid)
betas<-getBeta(MSet.illumina)
Beta_melted<- melt(betas)
Beta_melted_raw<- melt(beta_raw)
#remove NAs before plotting (otherwise get many non-inifnite warnings)
Beta_Plot<-Beta_melted[which(!(is.na(Beta_melted$value))),]
Beta_Plot_raw<-Beta_melted_raw[which(!(is.na(Beta_melted_raw$value))),]
#add meta
colnames(Beta_Plot)<-c("CpG","ID","Beta")
Beta_Plot<-merge(Beta_Plot,sampleinfo_organoid, by.x="ID", by.y="Assay.Name")
colnames(Beta_Plot_raw)<-c("CpG","ID","Beta")
Beta_Plot_raw<-merge(Beta_Plot_raw,sampleinfo_organoid, by.x="ID", by.y="Assay.Name")
dis1<-ggplot(Beta_Plot, aes(Beta, group=as.character(ID), color=as.character(Characteristics.sampling.site.)))+
geom_density()+theme_bw()+xlab("DNAm Beta Value")
dis2<-ggplot(Beta_Plot_raw, aes(Beta, group=as.character(ID), color=as.character(Characteristics.sampling.site.)))+
geom_density()+theme_bw()+xlab("DNAm Beta Value")
ggsave(here("figs","MTAB4957_beta_distribution.pdf"), grid.arrange(dis1, dis2),w=20, h=5)
ggsave(here("figs/jpeg","MTAB4957_beta_distribution.jpeg"), grid.arrange(dis1, dis2), w=20, h=5)
MTAB_organoid_beta <- MTAB_organoid_beta[!grepl("rs",rownames(MTAB_organoid_beta)), ]
print(paste("Samples available: ",ncol(MTAB_organoid_beta),"\nProbes available: ",nrow(MTAB_organoid_beta),sep=""))
## [1] "Samples available: 134\nProbes available: 485512"
# https://emea.support.illumina.com/downloads/humanmethylation450_15017482_v1-2_product_files.html
anno_450k<-read.csv(here("data","HumanMethylation450_15017482_v1-2.csv"), skip=7)
anno_450k<-anno_450k[match(rownames(MTAB_organoid_beta),anno_450k$IlmnID),]
identical(rownames(MTAB_organoid_beta), anno_450k$IlmnID)
## [1] TRUE
MTAB_organoid_beta<-MTAB_organoid_beta[which(!(anno_450k$CHR%in%c('X','Y'))),]
filt_sex<-nrow(MTAB_organoid_beta)
print(paste("Samples available: ",ncol(MTAB_organoid_beta),"Probes available: ",nrow(MTAB_organoid_beta),sep=""))
## [1] "Samples available: 134Probes available: 473864"
Some probes have been found to cross-hybridize with other chromosomes (Price et al. 2013 Epigenetics). https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL16304
price<-read.table(here("data","GPL16304-47833.txt"), sep='\t', header=T, skip=22)
price<-price[match(rownames(MTAB_organoid_beta),price$ID),]
cross_hyb<-price[which(price$XY_Hits=="XY_YES" | price$Autosomal_Hits=="A_YES"),]
MTAB_organoid_beta<-MTAB_organoid_beta[which(!(rownames(MTAB_organoid_beta)%in%cross_hyb$ID)),]
filt_cross<-nrow(MTAB_organoid_beta)
print(paste("Samples available: ",ncol(MTAB_organoid_beta),"\nProbes available: ",nrow(MTAB_organoid_beta),sep=""))
## [1] "Samples available: 134\nProbes available: 433274"
Polymorphic probes
SnpatCpG<-price[which(price$Target.CpG.SNP!=""),]
MTAB_organoid_beta<-MTAB_organoid_beta[which(!(rownames(MTAB_organoid_beta)%in%SnpatCpG$ID)),]
filt_poly<-nrow(MTAB_organoid_beta)
print(paste("Samples available: ",ncol(MTAB_organoid_beta),"\nProbes available: ",nrow(MTAB_organoid_beta),sep=""))
## [1] "Samples available: 134\nProbes available: 415080"
Remove probes with high NA count
na_count_probe <-sapply(1:nrow(MTAB_organoid_beta), function(y) length(which(is.na(MTAB_organoid_beta[y,]))))
na_count_probe_good<-which(na_count_probe<(ncol(MTAB_organoid_beta)*0.05))
MTAB_organoid_beta<-MTAB_organoid_beta[na_count_probe_good,]
filt_bead<-nrow(MTAB_organoid_beta)
print(paste("Samples available: ",ncol(MTAB_organoid_beta),"\nProbes available: ",nrow(MTAB_organoid_beta),sep=""))
## [1] "Samples available: 134\nProbes available: 415080"
Remove probes with high detection p value across samples, and any samples with many high detection p value probes
detP <- detectionP(rgset_organoid)
failed <- detP>0.05
bad_det_p<-names(which(rowMeans(failed)>0.01))
bad_det_psamp<-names(which(colMeans(failed)>0.01))
MTAB_organoid_beta<-MTAB_organoid_beta[which(!(rownames(MTAB_organoid_beta)%in%bad_det_p)),]
MTAB_organoid_beta<-MTAB_organoid_beta[,which(!(colnames(MTAB_organoid_beta)%in%bad_det_psamp))]
filt_detp<-nrow(MTAB_organoid_beta)
print(paste("Samples available: ",ncol(MTAB_organoid_beta),"\nProbes available: ",nrow(MTAB_organoid_beta),sep=""))
## [1] "Samples available: 134\nProbes available: 409528"
save(MTAB_organoid_beta, sampleinfo_organoid, file=paste(here("data"),"/MTAB4957_beta_organoids.RData",sep=""))
#load(here("data", "MTAB4957_beta_organoids.RData"))
sampleinfo_organoid<-sampleinfo_organoid[,c(1:16,24:27)]
identical(colnames(MTAB_organoid_beta),sampleinfo_organoid$Assay.Name)
## [1] TRUE
head(sampleinfo_organoid)
## Source.Name Material.Type Characteristics.organism.
## 1 P1 organism part Homo sapiens
## 2 P2 organism part Homo sapiens
## 3 P3 organism part Homo sapiens
## 4 P4 organism part Homo sapiens
## 5 P5 organism part Homo sapiens
## 6 P6 organism part Homo sapiens
## Characteristics.individual. Characteristics.cell.type.
## 1 P1 organism part
## 2 P2 organism part
## 3 P3 organism part
## 4 P4 organism part
## 5 P5 organism part
## 6 P6 organism part
## Characteristics.biosource.type. Characteristics.developmental.stage.
## 1 organism part juvenile stage
## 2 organism part juvenile stage
## 3 organism part juvenile stage
## 4 organism part juvenile stage
## 5 organism part juvenile stage
## 6 organism part juvenile stage
## Characteristics.sampling.site. Characteristics.age. Unit.time.unit.
## 1 sigmoid colon 5 to 15 year
## 2 sigmoid colon 5 to 15 year
## 3 sigmoid colon 6 to 15 year
## 4 sigmoid colon 7 to 15 year
## 5 sigmoid colon 8 to 15 year
## 6 sigmoid colon 9 to 15 year
## Term.Source.REF Term.Accession.Number Characteristics.sex.
## 1 EFO UO_0000036 female
## 2 EFO UO_0000036 male
## 3 EFO UO_0000036 male
## 4 EFO UO_0000036 male
## 5 EFO UO_0000036 male
## 6 EFO UO_0000036 male
## Characteristics.passage. Comment..basename. Assay.Name
## 1 not applicable 5831583005_R01C01 5831583005_R01C01
## 2 not applicable 5831583005_R02C01 5831583005_R02C01
## 3 not applicable 5831583005_R03C01 5831583005_R03C01
## 4 not applicable 5831583005_R04C01 5831583005_R04C01
## 5 not applicable 5831583005_R05C01 5831583005_R05C01
## 6 not applicable 5831583005_R06C01 5831583005_R06C01
## Factor.Value..block. sentrix
## 1 5 5831583005
## 2 5 5831583005
## 3 5 5831583005
## 4 5 5831583005
## 5 5 5831583005
## 6 5 5831583005
## array.id.path
## 1 /nfs/research1/zerbino/redgar/DNAm_organoid_passage/data/published_organoids/E_MTAB_4957/5831583005_R01C01
## 2 /nfs/research1/zerbino/redgar/DNAm_organoid_passage/data/published_organoids/E_MTAB_4957/5831583005_R02C01
## 3 /nfs/research1/zerbino/redgar/DNAm_organoid_passage/data/published_organoids/E_MTAB_4957/5831583005_R03C01
## 4 /nfs/research1/zerbino/redgar/DNAm_organoid_passage/data/published_organoids/E_MTAB_4957/5831583005_R04C01
## 5 /nfs/research1/zerbino/redgar/DNAm_organoid_passage/data/published_organoids/E_MTAB_4957/5831583005_R05C01
## 6 /nfs/research1/zerbino/redgar/DNAm_organoid_passage/data/published_organoids/E_MTAB_4957/5831583005_R06C01
## det_pval
## 1 0.0009280434
## 2 0.0002483935
## 3 0.0003242456
## 4 0.0002260101
## 5 0.0002923051
## 6 0.0004080649
sampleinfo_ped_primary<-sampleinfo_organoid[which(sampleinfo_organoid$Characteristics.developmental.stage.=="juvenile stage" & sampleinfo_organoid$Characteristics.biosource.type.=="purified cell"),]
print(paste("Primary pediatric samples available: ",nrow(sampleinfo_ped_primary), sep=""))
## [1] "Primary pediatric samples available: 35"
# Three samples are the non-epithelial portion
sampleinfo_ped_primary<-sampleinfo_ped_primary[-grep("non-epithelial",sampleinfo_ped_primary$Characteristics.cell.type.),]
organoid_ped_primary<-MTAB_organoid_beta[,which(colnames(MTAB_organoid_beta)%in%sampleinfo_ped_primary$Assay.Name)]
identical(colnames(organoid_ped_primary),sampleinfo_ped_primary$Assay.Name)
## [1] TRUE
print(paste("Primary samples available: ",nrow(sampleinfo_ped_primary), sep=""))
## [1] "Primary samples available: 32"
sampleinfo_fetal_primary<-sampleinfo_organoid[which(sampleinfo_organoid$Characteristics.developmental.stage.=="fetal stage" & sampleinfo_organoid$Characteristics.biosource.type.=="purified cell"),]
print(paste("Primary fetal samples available: ",nrow(sampleinfo_fetal_primary), sep=""))
## [1] "Primary fetal samples available: 11"
organoid_fetal_primary<-MTAB_organoid_beta[,which(colnames(MTAB_organoid_beta)%in%sampleinfo_fetal_primary$Assay.Name)]
identical(colnames(organoid_fetal_primary),sampleinfo_fetal_primary$Assay.Name)
## [1] TRUE
print(paste("Primary samples available: ",nrow(sampleinfo_fetal_primary), sep=""))
## [1] "Primary samples available: 11"
sampleinfo_organoid<-sampleinfo_organoid[which(sampleinfo_organoid$Characteristics.biosource.type.=="organoid"),]
MTAB_organoid_beta<-MTAB_organoid_beta[,which(colnames(MTAB_organoid_beta)%in%sampleinfo_organoid$Assay.Name)]
identical(colnames(MTAB_organoid_beta),sampleinfo_organoid$Assay.Name)
## [1] TRUE
print(paste("Organoid samples available: ",nrow(sampleinfo_organoid), sep=""))
## [1] "Organoid samples available: 82"
sampleinfo_organoid$passage.or.rescope.no_numeric<-as.factor(as.character(sampleinfo_organoid$Characteristics.passage.))
levels(sampleinfo_organoid$passage.or.rescope.no_numeric)<-c(1,11,12,14,18,2,21,23,3,4,5,6,7,8,9)
sampleinfo_organoid$passage.or.rescope.no_numeric<-as.numeric(as.character(sampleinfo_organoid$passage.or.rescope.no_numeric))
sample_ID to include patient and tissue
sampleinfo_organoid$sample_ID<-paste(sampleinfo_organoid$Characteristics.individual., sampleinfo_organoid$Characteristics.sampling.site.)
remove AP as it seems to indicate a mixture of passages (i.e P1AP6)? These aen’t mentioned in manscript?
sampleinfo_organoid<-sampleinfo_organoid[-grep("AP",sampleinfo_organoid$Source.Name),]
Unclear what GM and IM are but it seems like only 281 was under these conditions, so will exclude to be safe
sampleinfo_organoid<-sampleinfo_organoid[-grep("281",sampleinfo_organoid$Source.Name),]
tidy condition
sampleinfo_organoid$condition<-NA
need to grep for WT and Clone B
sampleinfo_organoid$condition[grep("WT",sampleinfo_organoid$Source.Name)]<-"WT"
sampleinfo_organoid$condition[grep("Clone B|CloneB",sampleinfo_organoid$Source.Name)]<-"KO"
DM seems to be differenitated and SCM is maybe undifferentiated
sampleinfo_organoid$condition[grep("SCM",sampleinfo_organoid$Source.Name)]<-"SCM"
sampleinfo_organoid$condition[grep("DM",sampleinfo_organoid$Source.Name)]<-"DM4d"
print(paste("Organoid samples available: ",nrow(sampleinfo_organoid), sep=""))
## [1] "Organoid samples available: 70"
# match the DNAm data
MTAB_organoid_beta<-MTAB_organoid_beta[,which(colnames(MTAB_organoid_beta)%in%sampleinfo_organoid$Assay.Name)]
identical(colnames(MTAB_organoid_beta),sampleinfo_organoid$Assay.Name)
## [1] TRUE
Individuals “212” “223” “224” “225” “369” are in both studies. The organoids from these individuals will be removed from the differential DNAm analysis, but visulized later to show the patterns occur across array type Saving them for later integration
sampleinfo_organoid_paired<-sampleinfo_organoid[grep("212|223|224",sampleinfo_organoid$Characteristics.individual.),]
MTAB4957_beta_for_paird<-MTAB_organoid_beta[,which(colnames(MTAB_organoid_beta)%in%sampleinfo_organoid_paired$Assay.Name)]
identical(colnames(MTAB4957_beta_for_paird), sampleinfo_organoid_paired$Assay.Name)
## [1] TRUE
print(paste("Organoid samples available: ",nrow(sampleinfo_organoid_paired), sep=""))
## [1] "Organoid samples available: 16"
load the EPIC organoids
load(here("data","beta_organoids.RData"))
intersect(sampleinfo_organoid$Characteristics.individual., epic.organoid$case.no)
## [1] "212" "223" "224" "225" "369"
369 and 225 are run at identical passages in both cohorts so all samples will be removed.
sampleinfo_organoid[grep("369",sampleinfo_organoid$Characteristics.individual.),c(1,4,8,9,13,21,22)]
## Source.Name Characteristics.individual.
## 105 369 TI P3 SCM 369
## 106 369 TI P3 DM4d 369
## 108 369 SC P3 SCM 369
## 110 369 SC P3 DM4d 369
## Characteristics.sampling.site. Characteristics.age.
## 105 terminal ileum 9
## 106 terminal ileum 9
## 108 sigmoid colon 9
## 110 sigmoid colon 9
## Characteristics.sex. passage.or.rescope.no_numeric sample_ID
## 105 male 3 369 terminal ileum
## 106 male 3 369 terminal ileum
## 108 male 3 369 sigmoid colon
## 110 male 3 369 sigmoid colon
epic.organoid[grep("369",epic.organoid$case.no),c(1,5,17, 9, 10)]
## case.no sample.site passage.or.rescope.no_numeric sex age
## 22 369 SC 3 M 9
## 23 369 TI 3 M 9
sampleinfo_organoid<-sampleinfo_organoid[-grep("369|225",sampleinfo_organoid$Characteristics.individual.),]
212,223 and 224 have organoids at passages only used in MTAB-4957. So organoids that are included at the same passage will be removed.
remove_sampleID<-c("212 SC P6","212 TI P6","223 SC P2","223 TI P2","224 SC P3","224 TI P2")
sampleinfo_organoid<-sampleinfo_organoid[which(!(sampleinfo_organoid$Source.Name%in%remove_sampleID)),]
print(paste("Organoid samples available: ",nrow(sampleinfo_organoid), sep=""))
## [1] "Organoid samples available: 58"
# match the DNAm data
MTAB_organoid_beta<-MTAB_organoid_beta[,which(colnames(MTAB_organoid_beta)%in%sampleinfo_organoid$Assay.Name)]
identical(colnames(MTAB_organoid_beta),sampleinfo_organoid$Assay.Name)
## [1] TRUE
pca_res <- prcomp(t(MTAB_organoid_beta))
Loadings<-as.data.frame(pca_res$x)
vars <- pca_res$sdev^2
Importance<-vars/sum(vars)
meta_categorical <- sampleinfo_organoid[, c(4,7,8,13,17,18)] # input column numbers in meta that contain categorical variables
meta_continuous <- sampleinfo_organoid[, c(9,21)] # input column numbers in meta that contain continuous variables
colnames(meta_categorical) <- c("Individual", "Developmental Stage","Sample Site","Sex","Block","Sentrix ID")
colnames(meta_continuous) <- c("Age", "Passage")
meta_continuous$Age<-as.numeric(meta_continuous$Age)
meta_categorical$Block<-as.factor(meta_categorical$Block)
ord<-1:length(c(colnames(meta_categorical),colnames(meta_continuous)))
PCs_to_view<-10
suppressWarnings(heat_scree_plot(Loadings, Importance, 2.5, 2.7))
## PC vs PC plot
Loadings$Assay.Name<-rownames(Loadings)
Loadings_meta<-merge(Loadings, sampleinfo_organoid, by="Assay.Name")
ggplot(Loadings_meta, aes(PC1, PC2, fill=Characteristics.developmental.stage.))+geom_point(shape=21,size=3, color="black")+theme_bw()+
xlab(paste("PC1 (",round(Importance[1]*100,0),"%)", sep=""))+ylab(paste("PC2 (",round(Importance[2]*100,0),"%)", sep=""))+th+theme(axis.text = element_text(size=12),
axis.title = element_text(size=14),
plot.margin = margin(1, 0.1, 1, 1, "cm"))
ggplot(Loadings_meta, aes(PC1, PC2, fill=Characteristics.sampling.site.))+geom_point(shape=21,size=3, color="black")+theme_bw()+
xlab(paste("PC1 (",round(Importance[1]*100,0),"%)", sep=""))+ylab(paste("PC2 (",round(Importance[2]*100,0),"%)", sep=""))+th+theme(axis.text = element_text(size=12),
axis.title = element_text(size=14),
plot.margin = margin(1, 0.1, 1, 1, "cm"))
ggplot(Loadings_meta, aes(PC2, PC3, fill=Characteristics.sampling.site.))+geom_point(shape=21,size=3, color="black")+theme_bw()+
xlab(paste("PC1 (",round(Importance[1]*100,0),"%)", sep=""))+ylab(paste("PC2 (",round(Importance[2]*100,0),"%)", sep=""))+th+theme(axis.text = element_text(size=12),
axis.title = element_text(size=14),
plot.margin = margin(1, 0.1, 1, 1, "cm"))
pc_plt<-ggplot(Loadings_meta, aes(PC2, PC3, fill=as.factor(passage.or.rescope.no_numeric),color=Characteristics.developmental.stage.))+geom_line(aes(PC2,PC3, group=sample_ID), color="lightgrey")+#, color=sampling.time.point
geom_point(shape=21,size=3)+#
theme_bw()+xlab(paste("PC2 (",round(Importance[2]*100,0),"%)", sep=""))+ylab(paste("PC3 (",round(Importance[3]*100,0),"%)", sep=""))+th+theme(axis.text = element_text(size=12),axis.title = element_text(size=14))+
scale_fill_manual(values=pass_col,name="Passage\nNumber")+scale_color_manual(values=c("black","white","black"))
legend<-ggplot(sampleinfo_organoid, aes(as.factor(-passage.or.rescope.no_numeric), fill=as.factor(passage.or.rescope.no_numeric)))+geom_bar(color="black")+
theme_bw()+theme(legend.position = "none", axis.text.y = element_blank(),
axis.title.y = element_blank(),
axis.ticks.y = element_blank(),
legend.title=element_text(size=10),
legend.text=element_text(size=8))+
coord_flip()+
scale_fill_manual(values=pass_col,name="Passage\nNumber")+th
r <- ggplot() + theme_void()
grid.arrange(pc_plt,arrangeGrob(r,legend,r, heights=c(0.6,1.25,0.4)), ncol=2, widths=c(7,1))
High passage fetal toward older organoids?
ggplot(Loadings_meta, aes(PC1, PC2, fill=as.factor(passage.or.rescope.no_numeric), color=Characteristics.developmental.stage.))+geom_line(aes(PC1,PC2, group=sample_ID), color="lightgrey")+#, color=sampling.time.point
geom_point(shape=21,size=3)+#
theme_bw()+xlab(paste("PC1 (",round(Importance[1]*100,0),"%)", sep=""))+ylab(paste("PC2 (",round(Importance[2]*100,0),"%)", sep=""))+th+theme(axis.text = element_text(size=12),axis.title = element_text(size=14))+
scale_fill_manual(values=pass_col,name="Passage\nNumber")+scale_color_manual(values=c("black","white","black"))
sampleinfo_organoid_notfetal<-sampleinfo_organoid[which(sampleinfo_organoid$Characteristics.biosource.type.=="organoid" & sampleinfo_organoid$Characteristics.developmental.stage.!="fetal stage"),]
MTAB_organoid_beta_notfetal<-MTAB_organoid_beta[,which(colnames(MTAB_organoid_beta)%in%sampleinfo_organoid_notfetal$Assay.Name)]
identical(colnames(MTAB_organoid_beta_notfetal),sampleinfo_organoid_notfetal$Assay.Name)
## [1] TRUE
pca_res <- prcomp(t(MTAB_organoid_beta_notfetal))
Loadings<-as.data.frame(pca_res$x)
vars <- pca_res$sdev^2
Importance<-vars/sum(vars)
meta_categorical <- sampleinfo_organoid_notfetal[, c(4,7,8,13,17,18)] # input column numbers in meta that contain categorical variables
meta_continuous <- sampleinfo_organoid_notfetal[, c(9,21)] # input column numbers in meta that contain continuous variables
colnames(meta_categorical) <- c("Individual", "Developmental Stage","Sample Site","Sex","Block","Sentrix ID")
colnames(meta_continuous) <- c("Age", "Passage")
meta_continuous$Age<-as.numeric(meta_continuous$Age)
meta_categorical$Block<-as.factor(meta_categorical$Block)
ord<-1:length(c(colnames(meta_categorical),colnames(meta_continuous)))
PCs_to_view<-10
suppressWarnings(heat_scree_plot(Loadings, Importance, 2.5, 2.7))
## PC vs PC plot
Loadings$Assay.Name<-rownames(Loadings)
Loadings_meta<-merge(Loadings, sampleinfo_organoid_notfetal, by="Assay.Name")
Sample Site
ggplot(Loadings_meta, aes(PC1, PC2, fill=Characteristics.sampling.site.))+geom_point(shape=21,size=3, color="black")+theme_bw()+
xlab(paste("PC1 (",round(Importance[1]*100,0),"%)", sep=""))+ylab(paste("PC2 (",round(Importance[2]*100,0),"%)", sep=""))+th+theme(axis.text = element_text(size=12),
axis.title = element_text(size=14),
plot.margin = margin(1, 0.1, 1, 1, "cm"))
Condition
ggplot(Loadings_meta, aes(PC1, PC2, fill=condition))+geom_point(shape=21,size=3, color="black")+theme_bw()+
xlab(paste("PC1 (",round(Importance[1]*100,0),"%)", sep=""))+ylab(paste("PC2 (",round(Importance[2]*100,0),"%)", sep=""))+th+theme(axis.text = element_text(size=12),
axis.title = element_text(size=14),
plot.margin = margin(1, 0.1, 1, 1, "cm"))
Sample Site PC2/3
ggplot(Loadings_meta, aes(PC2, PC3, fill=Characteristics.sampling.site.))+geom_point(shape=21,size=3, color="black")+theme_bw()+
xlab(paste("PC2 (",round(Importance[2]*100,0),"%)", sep=""))+ylab(paste("PC3 (",round(Importance[3]*100,0),"%)", sep=""))+th+theme(axis.text = element_text(size=12),
axis.title = element_text(size=14),
plot.margin = margin(1, 0.1, 1, 1, "cm"))
Sample Site PC3/4
ggplot(Loadings_meta, aes(PC3, PC4, fill=Characteristics.sampling.site.))+geom_point(shape=21,size=3, color="black")+theme_bw()+
xlab(paste("PC3 (",round(Importance[3]*100,0),"%)", sep=""))+ylab(paste("PC4 (",round(Importance[4]*100,0),"%)", sep=""))+th+theme(axis.text = element_text(size=12),
axis.title = element_text(size=14),
plot.margin = margin(1, 0.1, 1, 1, "cm"))
pc_plt<-ggplot(Loadings_meta, aes(PC2, PC3, fill=as.factor(passage.or.rescope.no_numeric)))+geom_line(aes(PC2,PC3, group=sample_ID), color="lightgrey")+#, color=sampling.time.point
geom_point(shape=21,size=3)+#
theme_bw()+xlab(paste("PC2 (",round(Importance[2]*100,0),"%)", sep=""))+ylab(paste("PC3 (",round(Importance[3]*100,0),"%)", sep=""))+th+theme(axis.text = element_text(size=12),axis.title = element_text(size=14))+
scale_fill_manual(values=pass_col,name="Passage\nNumber")+scale_color_manual(values=c("black","white","black"))
legend<-ggplot(sampleinfo_organoid_notfetal, aes(as.factor(-passage.or.rescope.no_numeric), fill=as.factor(passage.or.rescope.no_numeric)))+geom_bar(color="black")+
theme_bw()+theme(legend.position = "none", axis.text.y = element_blank(),
axis.title.y = element_blank(),
axis.ticks.y = element_blank(),
legend.title=element_text(size=10),
legend.text=element_text(size=8))+
coord_flip()+
scale_fill_manual(values=pass_col,name="Passage\nNumber")+th
r <- ggplot() + theme_void()
grid.arrange(pc_plt,arrangeGrob(r,legend,r, heights=c(0.6,1.25,0.4)), ncol=2, widths=c(7,1))
Variation<-function(x) {quantile(x, c(0.9), na.rm=T)[[1]]-quantile(x, c(0.1), na.rm=T)[[1]]}
Mval<-function(beta) log2(beta/(1-beta))
MTAB4957_mval= apply(MTAB_organoid_beta_notfetal, 1, Mval) # need mvalues for combat
MTAB4957_mval = as.data.frame(MTAB4957_mval)
MTAB4957_mval = t(MTAB4957_mval)
ref_range_dnam<-sapply(1:nrow(MTAB4957_mval), function(x) Variation(MTAB4957_mval[x,]))
dim(MTAB4957_beta_VeryVariable<-MTAB_organoid_beta_notfetal[which(ref_range_dnam>=2.75),])# 47924
## [1] 47924 30
## Beta distribution plot
Beta_melted<- melt(MTAB4957_beta_VeryVariable)
Beta_Plot<-Beta_melted[which(!(is.na(Beta_melted$value))),]
colnames(Beta_Plot)<-c("CpG","ID","Beta")
Beta_Plot<-merge(Beta_Plot,sampleinfo_organoid_notfetal, by.x="ID", by.y="Assay.Name")
Beta_Plot$passage.or.rescope.no_numeric.factor <- factor(Beta_Plot$passage.or.rescope.no_numeric, levels = c(11,9,8,6,4,3,2,1))
ggplot(Beta_Plot, aes(Beta,color=passage.or.rescope.no_numeric.factor))+
geom_density(size=1)+theme_bw()+xlab("DNAm Beta Value")+ylab("Density")+
scale_color_manual(values=pass_col, name="Passage\nNumber")+th+theme(legend.text = element_text(size=7),
legend.title = element_text(size=10),
legend.key.size = unit(0.7,"line"))
To view the beta distributions we will also include a line for the 32 primary samples to compare each passage to primary
MTAB4957_mval= apply(organoid_ped_primary, 1, Mval) # need mvalues for combat
MTAB4957_mval = as.data.frame(MTAB4957_mval)
MTAB4957_mval = t(MTAB4957_mval)
ref_range_dnam_primary<-sapply(1:nrow(MTAB4957_mval), function(x) Variation(MTAB4957_mval[x,]))
dim(organoid_ped_primary_VeryVariable<-organoid_ped_primary[rev(order(ref_range_dnam_primary)),])
## [1] 409528 32
Include the same number of vairable CpGs as organoids varible. So take the 47924 most variable
dim(organoid_ped_primary_VeryVariable<-organoid_ped_primary_VeryVariable[1:47924 ,])
## [1] 47924 32
Beta_melted_MTAB_primary<- melt(organoid_ped_primary_VeryVariable)
Beta_Plot_MTAB_primary<-Beta_melted_MTAB_primary[which(!(is.na(Beta_melted_MTAB_primary$value))),]
colnames(Beta_Plot_MTAB_primary)<-c("CpG","ID","Beta")
Beta_Plot_MTAB_primary<-merge(Beta_Plot_MTAB_primary,sampleinfo_ped_primary, by.x="ID", by.y="Assay.Name")
Beta_plot_primary<-Beta_Plot_MTAB_primary[,c(1:3)]
Beta_plot_primary$passage.or.rescope.no_numeric<-0
Beta_Plot<-Beta_Plot[,c(1:3,23)]
Beta_Plot_combined<-rbind(Beta_plot_primary,Beta_Plot)
Beta_Plot_combined$passage.or.rescope.no_numeric.factor <- factor(Beta_Plot_combined$passage.or.rescope.no_numeric, levels = c(11,9,8,6,4,3,2,1,0))
ggplot(Beta_Plot_combined, aes(Beta,color=as.factor(passage.or.rescope.no_numeric.factor)))+
geom_density(size=1)+theme_bw()+xlab("DNAm Beta Value")+ylab("Density")+
scale_color_manual(values=pass_col, name="Passage\nNumber")+th+theme(legend.text = element_text(size=7),
legend.title = element_text(size=10),
legend.key.size = unit(0.7,"line"))
ggsave(here("figs","MTAB4957_beta_notfetal_with_primary.pdf"),width = 3.75, height = 2.5)
ggsave(here("figs/jpeg","MTAB4957_beta_notfetal_with_primary.jpeg"), width = 3.75, height = 2.5)
These are just the from the individuals not shared across studies
sampleinfo_organoid_notfetal$sample.site<-as.factor(sampleinfo_organoid_notfetal$Characteristics.sampling.site.)
levels(sampleinfo_organoid_notfetal$sample.site)<-c("SC","TI")
sampleinfo_organoid_notfetal$sample_ID<-paste(sampleinfo_organoid_notfetal$Characteristics.individual., sampleinfo_organoid_notfetal$sample.site)
sampleinfo_organoid_paired_unique<-sampleinfo_organoid_notfetal[which(sampleinfo_organoid_notfetal$sample_ID%in%sampleinfo_organoid_notfetal$sample_ID[duplicated(sampleinfo_organoid_notfetal$sample_ID)]),]
MTAB4957.organoid_paired<-do.call(rbind,lapply(1:length(unique(sampleinfo_organoid_paired_unique$sample_ID)), function(x){
sample<-unique(sampleinfo_organoid_paired_unique$sample_ID)[x]
samp<-sampleinfo_organoid_paired_unique[sampleinfo_organoid_paired_unique$sample_ID==sample,]
samp<-samp[order(samp$passage.or.rescope.no_numeric),]
samp$hilo<-as.factor(samp$passage.or.rescope.no_numeric)
if(length(levels(samp$hilo))==2){levels(samp$hilo)<-c("lower","higher")}else{
if(length(levels(samp$hilo))==3){levels(samp$hilo)<-c("lower","higher","highest")}else{
if(length(levels(samp$hilo))==4){levels(samp$hilo)<-c("lowest","lower","higher","highest")}else{samp$hilo<-NA}
}
}
samp
}))
MTAB4957.organoid_paired<-MTAB4957.organoid_paired[which(!is.na(MTAB4957.organoid_paired$hilo)),]
## will include 224 in the combined plot with its passage 2,3 samples that were on the epic
MTAB4957.organoid_paired<-MTAB4957.organoid_paired[-(grep("224", MTAB4957.organoid_paired$Source.Name)),]
MTAB4957_beta_VeryVariable_paird<-MTAB4957_beta_VeryVariable[,which(sampleinfo_organoid_notfetal$sample_ID%in%MTAB4957.organoid_paired$sample_ID)]
Beta_melted<- melt(MTAB4957_beta_VeryVariable_paird)
Beta_Plot<-Beta_melted[which(!(is.na(Beta_melted$value))),]
colnames(Beta_Plot)<-c("CpG","ID","Beta")
Beta_Plot<-merge(Beta_Plot,MTAB4957.organoid_paired, by.x="ID", by.y="Assay.Name")
labels<-as.data.frame(tapply(MTAB4957.organoid_paired$passage.or.rescope.no_numeric, MTAB4957.organoid_paired$sample_ID, function(x) paste(x, collapse=", ")))
colnames(labels)<-"passge"
labels$sample_ID<-rownames(labels)
ggplot()+
geom_density(aes(Beta,color=hilo, group=ID),Beta_Plot, size=0.75)+theme_bw()+xlab("DNAm Beta Value")+ylab("Density")+
scale_color_manual(values = c ("#9ecae1", "#225ea8", "#081d58"), name="Relative\nPassage\nLevel within\nPatient")+facet_wrap(~sample_ID, nrow=1)+
geom_text(aes(0.75, 2.75, label=passge), data=labels, color="grey20")+th+theme(strip.text = element_text(size = 10),
axis.text=element_text(size=4),
panel.spacing = unit(0.7, "lines"))+th+
scale_x_continuous(breaks = c(0,0.5,1))
ggsave(here("figs","MTAB4957_beta_paired_notfetal.pdf"),width = 5, height = 2.2)
ggsave(here("figs/jpeg","MTAB4957_beta_paired_notfetal.jpeg"), width = 5, height = 2.2)
these are individuals present in both studies
intersect(sampleinfo_organoid_paired$Characteristics.individual., epic.organoid$case.no)
## [1] "212" "223" "224"
organoid_Mval = apply(organoid_beta, 1, Mval) # need mvalues for combat
organoid_Mval = as.data.frame(organoid_Mval)
organoid_Mval = t(organoid_Mval)
ref_range_dnam<-sapply(1:nrow(organoid_Mval), function(x) Variation(organoid_Mval[x,]))
organoid_beta_VeryVariable<-organoid_beta[which(ref_range_dnam>=2.75),]# 51545
“212” “223” “224” in both studes
epic.organoid_paired<-epic.organoid[grep("212|223|224",epic.organoid$case.no),]
MTAB4957_beta_VeryVariable_paird<-MTAB4957_beta_for_paird[which(rownames(MTAB4957_beta_for_paird)%in%rownames(MTAB4957_beta_VeryVariable)),]
identical(colnames(MTAB4957_beta_VeryVariable_paird), as.character(sampleinfo_organoid_paired$Assay.Name))
## [1] TRUE
epic.organoid_beta_VeryVariable_paird<-organoid_beta_VeryVariable[,which(colnames(organoid_beta_VeryVariable)%in%epic.organoid_paired$array.id)]
epic.organoid_beta_VeryVariable_paird<-epic.organoid_beta_VeryVariable_paird[,match(epic.organoid_paired$array.id,colnames(epic.organoid_beta_VeryVariable_paird))]
identical(colnames(epic.organoid_beta_VeryVariable_paird), as.character(epic.organoid_paired$array.id))
## [1] TRUE
epic.organoid_paired$Study<-"Cohort 1 Organoids"
sampleinfo_organoid_paired$Study<-"Cohort 2"
sampleinfo_organoid_paired$sample_ID<-gsub(" sigmoid colon", " SC",sampleinfo_organoid_paired$sample_ID)
sampleinfo_organoid_paired$sample_ID<-gsub(" terminal ileum", " TI",sampleinfo_organoid_paired$sample_ID)
colnames(sampleinfo_organoid_paired)[c(4,16)]<-c("case.no","array.id")
samplinfo_paired_combined<-rbind(epic.organoid_paired[,c(1,2,14,17,18)],sampleinfo_organoid_paired[,c(4,16,22,21,24)])
variable_beta_combined<-merge(epic.organoid_beta_VeryVariable_paird,MTAB4957_beta_VeryVariable_paird, by="row.names")
variable_beta_combined$Row.names<-NULL
identical(colnames(variable_beta_combined), as.character(samplinfo_paired_combined$array.id))
## [1] TRUE
samplinfo_paired_combined<-do.call(rbind,lapply(1:length(unique(samplinfo_paired_combined$sample_ID)), function(x){
sample<-unique(samplinfo_paired_combined$sample_ID)[x]
samp<-samplinfo_paired_combined[samplinfo_paired_combined$sample_ID==sample,]
samp<-samp[order(samp$passage.or.rescope.no_numeric),]
samp$hilo<-as.factor(samp$passage.or.rescope.no_numeric)
if(length(levels(samp$hilo))==2){levels(samp$hilo)<-c("lower","higher")}else{
if(length(levels(samp$hilo))==3){levels(samp$hilo)<-c("lower","higher","highest")}else{
if(length(levels(samp$hilo))==4){levels(samp$hilo)<-c("lowest","lower","higher","highest")}else{samp$hilo<-NA}
}
}
samp
}))
Beta_melted<- melt(variable_beta_combined)
## No id variables; using all as measure variables
Beta_Plot<-Beta_melted[which(!(is.na(Beta_melted$value))),]
colnames(Beta_Plot)<-c("ID","Beta")
Beta_Plot<-merge(Beta_Plot,samplinfo_paired_combined, by.x="ID", by.y="array.id")
Beta_Plot$hilo_epic<-paste(Beta_Plot$hilo,"\n", Beta_Plot$Study, sep="")
Beta_Plot$hilo_epic[grep("lower\nCohort 1 Organoids", Beta_Plot$hilo_epic)]<-"lower\nCohort 1"
Beta_Plot$hilo_epic<-factor(Beta_Plot$hilo_epic, levels=c("lower\nCohort 1", "lower\nCohort 2", "higher\nCohort 2", "highest\nCohort 2"))
labels<-as.data.frame(tapply(samplinfo_paired_combined$passage.or.rescope.no_numeric, list(samplinfo_paired_combined$sample_ID,samplinfo_paired_combined$Study), function(x) paste(x, collapse=", ")))
labels$sample_ID<-rownames(labels)
labels$MTAB<-paste("Cohort 2: ", labels$`Cohort 2`, sep="")
labels$OG<-paste("Cohort 1: ", labels$`Cohort 1 Organoids`, sep="")
ggplot()+
geom_density(aes(Beta,color=hilo_epic, group=ID),Beta_Plot, size=0.75)+theme_bw()+xlab("DNAm Beta Value")+ylab("Density")+
scale_color_manual(values = c ("#ef3b2c", "#9ecae1","#225ea8","#081d58"), name="Relative\nPassage\nLevel within\nPatient")+facet_wrap(~sample_ID, nrow=3)+
geom_text(aes(0.5, 2.55, label=MTAB), data=labels, color="grey20", size=2.75)+
geom_text(aes(0.456, 2.25, label=OG), data=labels, color="grey20", size=2.75)+
th+theme(strip.text = element_text(size = 12),
axis.text=element_text(size=10),
panel.spacing = unit(0.7, "lines"),
legend.text=element_text(size=9.5),
legend.title=element_text(size=12))+ scale_x_continuous(breaks = c(0,0.5,1))
ggsave(here("figs","MTAB4957_EPIC_beta_paired.pdf"),width = 6, height = 6)
ggsave(here("figs/jpeg","MTAB4957_EPIC_beta_paired.jpeg"), width = 6, height = 6)
sampleinfo_organoid_notfetal$thresholded_prior_ratio<-sapply(1:nrow(sampleinfo_organoid_notfetal), function(x){
print(x)
converted<-as.numeric(round(MTAB4957_beta_VeryVariable[,x]*1000,0))
counts<-rep(1000, length(converted))
res = em(converted, counts, .41, .31, .27, 0.01, .1, .1, .90, .03, .5, .05)
passage_threshold_params(converted, counts, res)
})
## [1] 1
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -270103.38 0.60 0.23 0.15 0.02 0.16
## [7] 0.09 0.87 0.04 0.51 0.05
## [1] -265610.50 0.65 0.20 0.12 0.03 0.18
## [7] 0.10 0.85 0.04 0.51 0.04
## [1] -264849.45 0.66 0.19 0.11 0.04 0.20
## [7] 0.11 0.84 0.04 0.52 0.04
## [1] -264579.20 0.67 0.18 0.10 0.04 0.21
## [7] 0.11 0.83 0.04 0.52 0.04
## [1] -264483.85 0.67 0.18 0.10 0.05 0.21
## [7] 0.12 0.83 0.04 0.52 0.04
## [1] -264462.54 0.67 0.18 0.10 0.05 0.22
## [7] 0.12 0.82 0.05 0.53 0.04
## [1] -264472.22 0.67 0.18 0.10 0.06 0.22
## [7] 0.12 0.82 0.05 0.53 0.04
## [1] 2
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -267948.50 0.57 0.28 0.12 0.02 0.14
## [7] 0.09 0.87 0.04 0.50 0.05
## [1] -265150.42 0.62 0.26 0.09 0.03 0.15
## [7] 0.10 0.85 0.04 0.51 0.04
## [1] -264649.49 0.64 0.25 0.08 0.04 0.15
## [7] 0.11 0.84 0.05 0.51 0.04
## [1] -264426.43 0.64 0.24 0.07 0.04 0.16
## [7] 0.11 0.83 0.05 0.51 0.04
## [1] -264304.19 0.65 0.24 0.07 0.05 0.16
## [7] 0.11 0.82 0.05 0.51 0.04
## [1] -264228.23 0.65 0.24 0.06 0.05 0.16
## [7] 0.11 0.82 0.05 0.51 0.04
## [1] -264174.45 0.64 0.24 0.06 0.06 0.16
## [7] 0.11 0.81 0.05 0.51 0.04
## [1] -264131.03 0.64 0.23 0.06 0.06 0.16
## [7] 0.11 0.81 0.05 0.51 0.04
## [1] -264091.61 0.64 0.23 0.06 0.07 0.16
## [7] 0.11 0.80 0.06 0.51 0.04
## [1] -264052.64 0.63 0.23 0.06 0.07 0.16
## [7] 0.11 0.80 0.06 0.51 0.04
## [1] -264012.18 0.63 0.23 0.06 0.08 0.15
## [7] 0.11 0.80 0.06 0.51 0.04
## [1] -263969.23 0.63 0.23 0.06 0.08 0.15
## [7] 0.10 0.79 0.06 0.51 0.04
## [1] -263923.51 0.62 0.23 0.06 0.08 0.15
## [7] 0.10 0.79 0.06 0.51 0.04
## [1] -263875.00 0.62 0.23 0.06 0.09 0.15
## [7] 0.10 0.79 0.06 0.51 0.05
## [1] -263824.06 0.61 0.23 0.06 0.09 0.15
## [7] 0.10 0.79 0.06 0.51 0.05
## [1] -263771.15 0.61 0.23 0.06 0.09 0.15
## [7] 0.10 0.79 0.06 0.51 0.05
## [1] -263716.82 0.61 0.23 0.06 0.10 0.15
## [7] 0.10 0.79 0.06 0.51 0.05
## [1] -263661.61 0.60 0.23 0.07 0.10 0.14
## [7] 0.10 0.79 0.06 0.50 0.05
## [1] -263606.08 0.60 0.23 0.07 0.10 0.14
## [7] 0.09 0.79 0.06 0.50 0.05
## [1] -263550.73 0.59 0.23 0.07 0.11 0.14
## [7] 0.09 0.79 0.06 0.50 0.05
## [1] -263496.13 0.59 0.23 0.07 0.11 0.14
## [7] 0.09 0.79 0.06 0.50 0.05
## [1] -263442.33 0.59 0.23 0.07 0.11 0.14
## [7] 0.09 0.79 0.06 0.50 0.06
## [1] -263389.84 0.58 0.23 0.07 0.12 0.14
## [7] 0.09 0.79 0.06 0.50 0.06
## [1] -263338.89 0.58 0.23 0.07 0.12 0.13
## [7] 0.09 0.79 0.06 0.49 0.06
## [1] -263289.68 0.57 0.23 0.07 0.12 0.13
## [7] 0.09 0.79 0.06 0.49 0.06
## [1] -263242.36 0.57 0.23 0.07 0.13 0.13
## [7] 0.08 0.79 0.06 0.49 0.06
## [1] -263197.03 0.57 0.23 0.08 0.13 0.13
## [7] 0.08 0.79 0.06 0.49 0.06
## [1] -263153.75 0.56 0.23 0.08 0.13 0.13
## [7] 0.08 0.79 0.06 0.49 0.06
## [1] -263112.73 0.56 0.23 0.08 0.14 0.13
## [7] 0.08 0.79 0.06 0.48 0.06
## [1] -263073.78 0.55 0.23 0.08 0.14 0.13
## [7] 0.08 0.79 0.06 0.48 0.06
## [1] -263036.82 0.55 0.22 0.08 0.14 0.12
## [7] 0.08 0.79 0.06 0.48 0.07
## [1] -263002.04 0.55 0.22 0.08 0.15 0.12
## [7] 0.08 0.79 0.06 0.48 0.07
## [1] -262969.40 0.54 0.22 0.08 0.15 0.12
## [7] 0.07 0.79 0.06 0.47 0.07
## [1] -262938.87 0.54 0.22 0.08 0.16 0.12
## [7] 0.07 0.79 0.07 0.47 0.07
## [1] -262910.43 0.53 0.22 0.09 0.16 0.12
## [7] 0.07 0.79 0.07 0.47 0.07
## [1] -262884.05 0.53 0.22 0.09 0.16 0.12
## [7] 0.07 0.79 0.07 0.47 0.07
## [1] -262859.71 0.53 0.22 0.09 0.17 0.11
## [7] 0.07 0.79 0.07 0.47 0.07
## [1] -262837.35 0.52 0.22 0.09 0.17 0.11
## [7] 0.07 0.79 0.07 0.46 0.07
## [1] -262816.93 0.52 0.22 0.09 0.17 0.11
## [7] 0.06 0.79 0.07 0.46 0.07
## [1] -262798.47 0.51 0.22 0.09 0.18 0.11
## [7] 0.06 0.79 0.07 0.46 0.08
## [1] -262782.05 0.51 0.22 0.09 0.18 0.11
## [7] 0.06 0.79 0.07 0.46 0.08
## [1] -262767.53 0.50 0.21 0.10 0.19 0.11
## [7] 0.06 0.79 0.07 0.46 0.08
## [1] -262754.77 0.50 0.21 0.10 0.19 0.11
## [7] 0.06 0.79 0.07 0.45 0.08
## [1] -262743.78 0.50 0.21 0.10 0.19 0.10
## [7] 0.06 0.79 0.07 0.45 0.08
## [1] -262734.60 0.49 0.21 0.10 0.20 0.10
## [7] 0.06 0.79 0.07 0.45 0.08
## [1] 3
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -265933.53 0.55 0.26 0.16 0.02 0.14
## [7] 0.08 0.89 0.04 0.51 0.04
## [1] -263730.92 0.60 0.24 0.13 0.03 0.14
## [7] 0.08 0.88 0.05 0.51 0.04
## [1] -263609.69 0.62 0.23 0.12 0.04 0.14
## [7] 0.07 0.88 0.05 0.51 0.04
## [1] -263566.97 0.64 0.21 0.11 0.04 0.13
## [7] 0.07 0.88 0.05 0.51 0.04
## [1] -263529.40 0.64 0.20 0.10 0.05 0.13
## [7] 0.06 0.88 0.05 0.51 0.04
## [1] -263491.42 0.65 0.20 0.10 0.06 0.12
## [7] 0.06 0.88 0.05 0.51 0.04
## [1] -263454.75 0.65 0.19 0.09 0.07 0.12
## [7] 0.05 0.88 0.05 0.51 0.04
## [1] -263426.41 0.65 0.19 0.09 0.07 0.11
## [7] 0.04 0.88 0.05 0.51 0.04
## [1] -263411.13 0.65 0.18 0.09 0.08 0.10
## [7] 0.04 0.88 0.05 0.51 0.04
## [1] -263413.40 0.65 0.18 0.09 0.08 0.10
## [7] 0.03 0.88 0.04 0.51 0.04
## [1] 4
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -268327.69 0.57 0.27 0.13 0.02 0.14
## [7] 0.08 0.88 0.04 0.50 0.05
## [1] -265055.63 0.62 0.26 0.10 0.03 0.15
## [7] 0.09 0.86 0.05 0.51 0.04
## [1] -264657.68 0.64 0.25 0.08 0.04 0.16
## [7] 0.09 0.85 0.05 0.51 0.04
## [1] -264483.42 0.64 0.24 0.07 0.04 0.16
## [7] 0.09 0.85 0.05 0.51 0.04
## [1] -264375.78 0.65 0.23 0.07 0.05 0.16
## [7] 0.09 0.84 0.06 0.51 0.04
## [1] -264295.85 0.65 0.23 0.06 0.06 0.16
## [7] 0.09 0.83 0.06 0.51 0.04
## [1] -264228.76 0.65 0.23 0.06 0.06 0.16
## [7] 0.09 0.83 0.06 0.51 0.04
## [1] -264167.37 0.65 0.23 0.06 0.07 0.16
## [7] 0.09 0.83 0.06 0.51 0.04
## [1] -264108.90 0.64 0.23 0.06 0.07 0.16
## [7] 0.09 0.82 0.06 0.51 0.04
## [1] -264051.78 0.64 0.23 0.06 0.07 0.16
## [7] 0.09 0.82 0.06 0.51 0.04
## [1] -263995.16 0.64 0.23 0.06 0.08 0.16
## [7] 0.09 0.82 0.06 0.51 0.04
## [1] -263938.68 0.64 0.22 0.06 0.08 0.15
## [7] 0.08 0.82 0.06 0.51 0.04
## [1] -263882.45 0.63 0.22 0.06 0.08 0.15
## [7] 0.08 0.82 0.07 0.51 0.04
## [1] -263826.28 0.63 0.22 0.06 0.09 0.15
## [7] 0.08 0.81 0.07 0.51 0.05
## [1] -263770.51 0.63 0.22 0.06 0.09 0.15
## [7] 0.08 0.81 0.07 0.51 0.05
## [1] -263715.49 0.62 0.22 0.06 0.09 0.15
## [7] 0.08 0.81 0.07 0.51 0.05
## [1] -263661.54 0.62 0.22 0.06 0.10 0.15
## [7] 0.08 0.81 0.07 0.51 0.05
## [1] -263609.02 0.62 0.22 0.06 0.10 0.15
## [7] 0.08 0.81 0.07 0.51 0.05
## [1] -263558.22 0.61 0.22 0.06 0.10 0.14
## [7] 0.07 0.81 0.07 0.50 0.05
## [1] -263509.50 0.61 0.22 0.06 0.11 0.14
## [7] 0.07 0.81 0.07 0.50 0.05
## [1] -263462.88 0.61 0.22 0.06 0.11 0.14
## [7] 0.07 0.81 0.07 0.50 0.05
## [1] -263418.64 0.60 0.22 0.07 0.11 0.14
## [7] 0.07 0.81 0.07 0.50 0.06
## [1] -263376.90 0.60 0.22 0.07 0.12 0.14
## [7] 0.07 0.81 0.07 0.50 0.06
## [1] -263337.76 0.59 0.22 0.07 0.12 0.14
## [7] 0.07 0.81 0.07 0.49 0.06
## [1] -263301.26 0.59 0.22 0.07 0.13 0.13
## [7] 0.07 0.81 0.07 0.49 0.06
## [1] -263267.41 0.59 0.22 0.07 0.13 0.13
## [7] 0.06 0.81 0.07 0.49 0.06
## [1] -263236.20 0.58 0.21 0.07 0.13 0.13
## [7] 0.06 0.81 0.07 0.49 0.06
## [1] -263207.60 0.58 0.21 0.07 0.14 0.13
## [7] 0.06 0.81 0.07 0.49 0.06
## [1] -263181.58 0.58 0.21 0.07 0.14 0.13
## [7] 0.06 0.81 0.07 0.48 0.07
## [1] -263158.07 0.57 0.21 0.07 0.14 0.13
## [7] 0.06 0.81 0.07 0.48 0.07
## [1] -263137.02 0.57 0.21 0.07 0.15 0.13
## [7] 0.06 0.81 0.07 0.48 0.07
## [1] -263118.37 0.56 0.21 0.08 0.15 0.12
## [7] 0.06 0.81 0.07 0.48 0.07
## [1] -263102.03 0.56 0.21 0.08 0.15 0.12
## [7] 0.06 0.81 0.07 0.48 0.07
## [1] -263087.93 0.56 0.21 0.08 0.16 0.12
## [7] 0.05 0.81 0.07 0.47 0.07
## [1] -263076.02 0.55 0.21 0.08 0.16 0.12
## [7] 0.05 0.81 0.07 0.47 0.07
## [1] -263066.20 0.55 0.21 0.08 0.17 0.12
## [7] 0.05 0.81 0.07 0.47 0.07
## [1] 5
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -263896.17 0.53 0.28 0.17 0.02 0.13
## [7] 0.08 0.89 0.03 0.51 0.04
## [1] -262305.00 0.57 0.26 0.15 0.03 0.13
## [7] 0.08 0.88 0.03 0.51 0.04
## [1] -262396.01 0.59 0.25 0.13 0.04 0.13
## [7] 0.08 0.88 0.03 0.52 0.03
## [1] -262563.43 0.60 0.24 0.12 0.04 0.12
## [7] 0.07 0.88 0.03 0.52 0.03
## [1] -262741.61 0.60 0.23 0.12 0.05 0.12
## [7] 0.07 0.89 0.03 0.52 0.03
## [1] -262910.45 0.60 0.23 0.11 0.06 0.12
## [7] 0.06 0.89 0.03 0.52 0.03
## [1] -263061.11 0.60 0.22 0.11 0.07 0.11
## [7] 0.06 0.89 0.03 0.52 0.03
## [1] -263187.95 0.60 0.22 0.11 0.07 0.11
## [7] 0.05 0.89 0.02 0.52 0.03
## [1] -263288.70 0.60 0.21 0.11 0.08 0.11
## [7] 0.05 0.89 0.02 0.52 0.03
## [1] -263365.51 0.60 0.21 0.11 0.08 0.10
## [7] 0.05 0.89 0.02 0.52 0.03
## [1] -263418.72 0.60 0.21 0.11 0.08 0.10
## [7] 0.05 0.89 0.02 0.52 0.03
## [1] -263453.60 0.60 0.21 0.11 0.09 0.10
## [7] 0.04 0.89 0.02 0.52 0.03
## [1] -263473.93 0.60 0.21 0.11 0.09 0.10
## [7] 0.04 0.90 0.02 0.52 0.03
## [1] -263482.87 0.60 0.20 0.10 0.09 0.09
## [7] 0.04 0.90 0.02 0.52 0.03
## [1] 6
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -262708.15 0.52 0.31 0.15 0.02 0.12
## [7] 0.08 0.89 0.03 0.51 0.04
## [1] -261310.86 0.55 0.30 0.12 0.03 0.11
## [7] 0.07 0.89 0.03 0.51 0.03
## [1] -261345.87 0.57 0.29 0.10 0.04 0.11
## [7] 0.06 0.89 0.03 0.51 0.03
## [1] -261458.68 0.58 0.28 0.09 0.05 0.10
## [7] 0.05 0.89 0.03 0.51 0.03
## [1] -261604.18 0.59 0.27 0.09 0.06 0.09
## [7] 0.04 0.90 0.03 0.51 0.03
## [1] -261760.99 0.59 0.26 0.08 0.07 0.09
## [7] 0.04 0.90 0.02 0.51 0.03
## [1] -261915.76 0.59 0.25 0.08 0.07 0.08
## [7] 0.03 0.90 0.02 0.51 0.03
## [1] -262059.79 0.60 0.25 0.08 0.08 0.08
## [7] 0.03 0.90 0.02 0.51 0.03
## [1] -262188.71 0.60 0.24 0.08 0.08 0.08
## [7] 0.02 0.91 0.02 0.51 0.03
## [1] -262301.69 0.60 0.24 0.07 0.09 0.07
## [7] 0.02 0.91 0.02 0.51 0.03
## [1] -262398.35 0.60 0.24 0.07 0.09 0.07
## [7] 0.02 0.91 0.02 0.51 0.03
## [1] -262478.14 0.60 0.23 0.07 0.09 0.07
## [7] 0.02 0.91 0.02 0.51 0.03
## [1] -262540.98 0.61 0.23 0.07 0.09 0.07
## [7] 0.02 0.91 0.01 0.51 0.04
## [1] -262587.79 0.61 0.23 0.07 0.10 0.07
## [7] 0.02 0.91 0.01 0.51 0.04
## [1] -262620.34 0.61 0.23 0.07 0.10 0.07
## [7] 0.02 0.91 0.01 0.50 0.04
## [1] -262640.65 0.61 0.22 0.07 0.10 0.07
## [7] 0.02 0.91 0.01 0.50 0.04
## [1] -262650.63 0.61 0.22 0.07 0.10 0.07
## [7] 0.02 0.91 0.01 0.50 0.04
## [1] 7
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -266156.99 0.55 0.23 0.20 0.02 0.14
## [7] 0.09 0.89 0.04 0.51 0.05
## [1] -263918.14 0.60 0.20 0.17 0.03 0.15
## [7] 0.09 0.88 0.04 0.52 0.04
## [1] -263719.46 0.62 0.19 0.16 0.03 0.16
## [7] 0.09 0.88 0.04 0.52 0.04
## [1] -263668.00 0.63 0.18 0.15 0.04 0.16
## [7] 0.09 0.87 0.04 0.53 0.04
## [1] -263651.32 0.64 0.17 0.15 0.04 0.16
## [7] 0.09 0.87 0.04 0.53 0.04
## [1] -263643.44 0.64 0.16 0.15 0.05 0.15
## [7] 0.09 0.87 0.04 0.54 0.04
## [1] 8
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -269727.89 0.59 0.24 0.15 0.02 0.16
## [7] 0.09 0.87 0.04 0.50 0.05
## [1] -265787.44 0.64 0.22 0.11 0.03 0.17
## [7] 0.10 0.86 0.05 0.51 0.04
## [1] -265125.41 0.66 0.21 0.10 0.04 0.19
## [7] 0.10 0.85 0.05 0.51 0.04
## [1] -264875.78 0.67 0.20 0.09 0.04 0.19
## [7] 0.11 0.84 0.05 0.52 0.04
## [1] -264777.19 0.67 0.20 0.09 0.05 0.20
## [7] 0.11 0.83 0.06 0.52 0.04
## [1] -264745.47 0.67 0.20 0.09 0.05 0.20
## [7] 0.11 0.82 0.06 0.52 0.04
## [1] -264743.71 0.67 0.19 0.08 0.05 0.21
## [7] 0.12 0.82 0.06 0.52 0.04
## [1] 9
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -269947.47 0.59 0.23 0.16 0.02 0.16
## [7] 0.09 0.87 0.03 0.51 0.05
## [1] -264782.87 0.63 0.20 0.14 0.03 0.17
## [7] 0.09 0.85 0.03 0.52 0.04
## [1] -264002.79 0.65 0.18 0.13 0.03 0.18
## [7] 0.09 0.84 0.04 0.53 0.04
## [1] -263744.75 0.66 0.17 0.13 0.04 0.19
## [7] 0.10 0.83 0.04 0.53 0.04
## [1] -263658.77 0.66 0.17 0.13 0.05 0.19
## [7] 0.10 0.83 0.04 0.54 0.04
## [1] -263640.91 0.66 0.17 0.13 0.05 0.19
## [7] 0.10 0.82 0.04 0.54 0.04
## [1] -263649.12 0.65 0.16 0.13 0.06 0.19
## [7] 0.10 0.82 0.04 0.54 0.04
## [1] 10
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -269866.23 0.59 0.25 0.14 0.02 0.15
## [7] 0.09 0.86 0.03 0.51 0.05
## [1] -265019.48 0.63 0.22 0.11 0.03 0.17
## [7] 0.09 0.85 0.04 0.51 0.04
## [1] -264281.88 0.65 0.21 0.10 0.04 0.17
## [7] 0.09 0.83 0.04 0.52 0.04
## [1] -264016.70 0.66 0.20 0.10 0.04 0.18
## [7] 0.10 0.83 0.04 0.52 0.04
## [1] -263913.05 0.66 0.20 0.10 0.05 0.18
## [7] 0.10 0.82 0.04 0.53 0.04
## [1] -263876.53 0.66 0.19 0.10 0.06 0.18
## [7] 0.10 0.81 0.04 0.53 0.04
## [1] -263867.28 0.65 0.19 0.10 0.06 0.18
## [7] 0.10 0.81 0.04 0.53 0.04
## [1] 11
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -269220.74 0.58 0.24 0.16 0.02 0.15
## [7] 0.09 0.86 0.03 0.51 0.05
## [1] -264457.82 0.62 0.22 0.13 0.03 0.16
## [7] 0.09 0.85 0.03 0.52 0.04
## [1] -263816.32 0.64 0.20 0.12 0.03 0.17
## [7] 0.09 0.84 0.03 0.52 0.04
## [1] -263619.25 0.64 0.20 0.12 0.04 0.17
## [7] 0.09 0.83 0.03 0.53 0.04
## [1] -263555.15 0.64 0.19 0.12 0.05 0.17
## [7] 0.09 0.83 0.04 0.53 0.04
## [1] -263537.61 0.64 0.19 0.12 0.05 0.17
## [7] 0.09 0.82 0.04 0.53 0.04
## [1] -263535.21 0.64 0.19 0.12 0.06 0.17
## [7] 0.09 0.82 0.04 0.53 0.04
## [1] 12
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -269547.80 0.58 0.26 0.14 0.02 0.14
## [7] 0.09 0.86 0.03 0.51 0.05
## [1] -264712.75 0.62 0.24 0.11 0.03 0.16
## [7] 0.09 0.84 0.03 0.52 0.04
## [1] -263961.59 0.64 0.22 0.10 0.04 0.16
## [7] 0.09 0.83 0.03 0.52 0.04
## [1] -263706.98 0.65 0.22 0.10 0.04 0.16
## [7] 0.09 0.82 0.04 0.53 0.04
## [1] -263619.22 0.65 0.21 0.09 0.05 0.16
## [7] 0.09 0.81 0.04 0.53 0.04
## [1] -263597.40 0.64 0.21 0.09 0.05 0.16
## [7] 0.09 0.81 0.04 0.53 0.04
## [1] -263600.38 0.64 0.21 0.09 0.06 0.16
## [7] 0.09 0.80 0.04 0.53 0.04
## [1] 13
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -259769.23 0.48 0.32 0.18 0.02 0.11
## [7] 0.07 0.90 0.03 0.51 0.03
## [1] -258078.74 0.50 0.31 0.16 0.03 0.10
## [7] 0.05 0.90 0.03 0.52 0.03
## [1] -257929.05 0.51 0.30 0.14 0.04 0.10
## [7] 0.05 0.90 0.03 0.53 0.02
## [1] -258104.90 0.52 0.30 0.14 0.05 0.09
## [7] 0.04 0.91 0.03 0.53 0.02
## [1] -258378.48 0.51 0.29 0.13 0.06 0.09
## [7] 0.04 0.91 0.02 0.53 0.02
## [1] -258619.09 0.51 0.29 0.13 0.07 0.08
## [7] 0.03 0.91 0.02 0.53 0.01
## [1] -258783.69 0.50 0.28 0.13 0.08 0.08
## [7] 0.03 0.91 0.02 0.53 0.01
## [1] -258876.56 0.50 0.28 0.13 0.09 0.08
## [7] 0.03 0.91 0.02 0.53 0.02
## [1] -258911.89 0.49 0.28 0.13 0.09 0.08
## [7] 0.03 0.91 0.02 0.53 0.02
## [1] -258909.71 0.49 0.28 0.13 0.10 0.08
## [7] 0.03 0.91 0.02 0.53 0.02
## [1] 14
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -259752.33 0.48 0.30 0.21 0.02 0.11
## [7] 0.07 0.90 0.03 0.52 0.04
## [1] -257997.02 0.50 0.29 0.19 0.02 0.11
## [7] 0.05 0.90 0.03 0.53 0.03
## [1] -257877.11 0.51 0.28 0.18 0.03 0.10
## [7] 0.05 0.91 0.03 0.53 0.02
## [1] -258059.72 0.52 0.27 0.17 0.05 0.10
## [7] 0.04 0.91 0.02 0.54 0.02
## [1] -258347.34 0.52 0.26 0.17 0.06 0.09
## [7] 0.03 0.91 0.02 0.54 0.02
## [1] -258622.45 0.51 0.26 0.16 0.07 0.09
## [7] 0.03 0.91 0.02 0.54 0.02
## [1] -258836.89 0.51 0.25 0.16 0.07 0.09
## [7] 0.03 0.91 0.02 0.54 0.01
## [1] -258972.88 0.51 0.25 0.16 0.08 0.09
## [7] 0.03 0.91 0.02 0.54 0.01
## [1] -259051.97 0.50 0.25 0.16 0.08 0.08
## [7] 0.03 0.91 0.02 0.54 0.01
## [1] -259083.13 0.50 0.25 0.16 0.09 0.08
## [7] 0.03 0.91 0.02 0.54 0.02
## [1] -259088.87 0.50 0.25 0.16 0.09 0.08
## [7] 0.03 0.91 0.02 0.55 0.02
## [1] 15
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -259682.08 0.48 0.32 0.19 0.02 0.11
## [7] 0.06 0.90 0.03 0.52 0.03
## [1] -257554.74 0.50 0.31 0.16 0.03 0.10
## [7] 0.05 0.90 0.03 0.53 0.03
## [1] -257281.93 0.51 0.31 0.15 0.04 0.09
## [7] 0.04 0.91 0.03 0.53 0.02
## [1] -257424.24 0.51 0.30 0.14 0.05 0.09
## [7] 0.03 0.91 0.03 0.54 0.02
## [1] -257696.08 0.51 0.29 0.14 0.06 0.09
## [7] 0.03 0.91 0.02 0.54 0.02
## [1] -257947.97 0.50 0.29 0.14 0.07 0.08
## [7] 0.03 0.91 0.02 0.54 0.01
## [1] -258121.06 0.49 0.29 0.14 0.08 0.08
## [7] 0.03 0.91 0.02 0.54 0.01
## [1] -258214.98 0.49 0.28 0.14 0.09 0.08
## [7] 0.03 0.91 0.02 0.54 0.01
## [1] -258247.70 0.49 0.28 0.14 0.09 0.08
## [7] 0.03 0.91 0.02 0.54 0.01
## [1] -258245.26 0.48 0.28 0.14 0.10 0.08
## [7] 0.03 0.91 0.02 0.55 0.01
## [1] 16
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -267714.39 0.56 0.23 0.20 0.02 0.16
## [7] 0.08 0.89 0.04 0.51 0.05
## [1] -263840.55 0.59 0.21 0.17 0.02 0.17
## [7] 0.07 0.88 0.04 0.52 0.04
## [1] -263510.94 0.61 0.20 0.16 0.03 0.17
## [7] 0.07 0.88 0.04 0.53 0.04
## [1] -263426.83 0.62 0.19 0.15 0.04 0.17
## [7] 0.07 0.87 0.05 0.53 0.04
## [1] -263404.13 0.63 0.18 0.15 0.04 0.17
## [7] 0.07 0.87 0.05 0.54 0.04
## [1] -263402.99 0.63 0.18 0.15 0.04 0.17
## [7] 0.07 0.87 0.05 0.54 0.04
## [1] 17
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -253828.02 0.42 0.34 0.22 0.01 0.09
## [7] 0.05 0.92 0.03 0.53 0.03
## [1] -249506.73 0.43 0.35 0.21 0.02 0.07
## [7] 0.03 0.93 0.02 0.54 0.02
## [1] -247643.30 0.42 0.34 0.20 0.04 0.06
## [7] 0.02 0.93 0.02 0.54 0.02
## [1] -247096.75 0.42 0.33 0.20 0.05 0.06
## [7] 0.02 0.93 0.01 0.55 0.01
## [1] -247104.69 0.41 0.33 0.19 0.07 0.06
## [7] 0.02 0.93 0.01 0.55 0.01
## [1] 18
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -268311.76 0.56 0.26 0.16 0.02 0.14
## [7] 0.08 0.87 0.04 0.51 0.05
## [1] -264655.97 0.60 0.24 0.13 0.03 0.15
## [7] 0.08 0.86 0.05 0.52 0.05
## [1] -264080.51 0.62 0.23 0.12 0.03 0.15
## [7] 0.08 0.85 0.05 0.52 0.04
## [1] -263871.65 0.63 0.22 0.11 0.04 0.15
## [7] 0.08 0.84 0.05 0.53 0.04
## [1] -263795.56 0.64 0.21 0.11 0.04 0.15
## [7] 0.08 0.83 0.05 0.53 0.04
## [1] -263775.52 0.64 0.21 0.11 0.04 0.15
## [7] 0.08 0.83 0.05 0.53 0.04
## [1] -263777.36 0.64 0.20 0.11 0.05 0.15
## [7] 0.08 0.82 0.06 0.53 0.04
## [1] 19
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -254974.48 0.43 0.34 0.22 0.01 0.09
## [7] 0.05 0.92 0.03 0.53 0.03
## [1] -250206.20 0.43 0.34 0.21 0.02 0.08
## [7] 0.03 0.93 0.02 0.54 0.02
## [1] -248591.60 0.43 0.34 0.20 0.03 0.07
## [7] 0.02 0.93 0.02 0.55 0.01
## [1] -248222.35 0.42 0.33 0.20 0.05 0.07
## [7] 0.02 0.93 0.02 0.55 0.01
## [1] -248282.61 0.41 0.33 0.19 0.07 0.07
## [7] 0.02 0.94 0.01 0.56 0.01
## [1] -248417.01 0.40 0.32 0.19 0.08 0.06
## [7] 0.02 0.94 0.01 0.56 0.01
## [1] -248490.51 0.40 0.32 0.19 0.09 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248504.56 0.39 0.32 0.19 0.09 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248483.83 0.39 0.32 0.19 0.09 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248447.40 0.39 0.32 0.20 0.10 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248407.71 0.39 0.32 0.20 0.10 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248374.19 0.38 0.32 0.20 0.10 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248340.00 0.38 0.32 0.20 0.10 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248309.41 0.38 0.32 0.20 0.10 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248282.71 0.38 0.32 0.20 0.10 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248259.42 0.38 0.32 0.20 0.10 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248239.13 0.38 0.32 0.20 0.10 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248221.50 0.38 0.32 0.20 0.10 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248206.19 0.38 0.32 0.20 0.10 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248192.91 0.37 0.32 0.20 0.10 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248181.34 0.37 0.32 0.20 0.10 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248171.27 0.37 0.32 0.20 0.11 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248166.53 0.37 0.32 0.20 0.11 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] 20
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -268423.74 0.56 0.26 0.16 0.02 0.15
## [7] 0.08 0.88 0.04 0.51 0.05
## [1] -264539.44 0.60 0.24 0.14 0.02 0.15
## [7] 0.08 0.86 0.05 0.51 0.05
## [1] -264042.09 0.62 0.23 0.13 0.03 0.16
## [7] 0.08 0.85 0.05 0.52 0.04
## [1] -263869.42 0.63 0.22 0.12 0.03 0.16
## [7] 0.08 0.85 0.05 0.52 0.04
## [1] -263802.11 0.63 0.22 0.12 0.04 0.16
## [7] 0.08 0.84 0.05 0.53 0.04
## [1] -263777.83 0.63 0.21 0.12 0.04 0.16
## [7] 0.07 0.84 0.06 0.53 0.04
## [1] -263770.78 0.63 0.21 0.11 0.04 0.15
## [7] 0.07 0.83 0.06 0.53 0.04
## [1] 21
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -269112.94 0.57 0.19 0.22 0.02 0.19
## [7] 0.06 0.90 0.04 0.50 0.05
## [1] -262778.77 0.60 0.18 0.19 0.02 0.21
## [7] 0.06 0.90 0.05 0.51 0.04
## [1] -262363.69 0.61 0.18 0.18 0.03 0.21
## [7] 0.05 0.90 0.05 0.52 0.04
## [1] -262336.88 0.62 0.17 0.17 0.04 0.22
## [7] 0.05 0.90 0.05 0.52 0.04
## [1] -262368.78 0.62 0.17 0.17 0.04 0.22
## [7] 0.05 0.90 0.05 0.53 0.04
## [1] -262403.04 0.62 0.17 0.17 0.05 0.22
## [7] 0.05 0.90 0.05 0.53 0.04
## [1] -262427.84 0.61 0.17 0.17 0.05 0.22
## [7] 0.05 0.90 0.04 0.53 0.04
## [1] -262440.14 0.61 0.17 0.16 0.06 0.22
## [7] 0.04 0.90 0.04 0.54 0.04
## [1] -262439.94 0.61 0.17 0.16 0.06 0.22
## [7] 0.04 0.90 0.04 0.54 0.04
## [1] 22
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -268870.79 0.57 0.22 0.20 0.02 0.15
## [7] 0.08 0.88 0.04 0.51 0.05
## [1] -264530.76 0.61 0.19 0.17 0.02 0.17
## [7] 0.08 0.86 0.04 0.52 0.05
## [1] -263860.41 0.63 0.18 0.17 0.03 0.17
## [7] 0.08 0.85 0.04 0.53 0.05
## [1] -263641.49 0.63 0.17 0.16 0.03 0.18
## [7] 0.08 0.85 0.05 0.54 0.04
## [1] -263574.84 0.64 0.16 0.16 0.04 0.18
## [7] 0.08 0.84 0.05 0.54 0.04
## [1] -263567.63 0.64 0.16 0.16 0.04 0.18
## [7] 0.08 0.84 0.05 0.55 0.04
## [1] 23
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -266085.21 0.54 0.26 0.18 0.02 0.14
## [7] 0.08 0.89 0.04 0.51 0.05
## [1] -263573.37 0.58 0.24 0.16 0.02 0.14
## [7] 0.08 0.89 0.05 0.51 0.04
## [1] -263440.72 0.60 0.23 0.14 0.03 0.14
## [7] 0.07 0.88 0.05 0.51 0.04
## [1] -263412.54 0.61 0.22 0.14 0.03 0.14
## [7] 0.07 0.88 0.05 0.52 0.04
## [1] -263398.10 0.62 0.21 0.13 0.04 0.14
## [7] 0.07 0.88 0.05 0.52 0.04
## [1] -263384.48 0.62 0.21 0.13 0.04 0.14
## [7] 0.07 0.88 0.05 0.52 0.04
## [1] -263368.42 0.63 0.20 0.12 0.04 0.13
## [7] 0.06 0.88 0.05 0.52 0.04
## [1] -263350.22 0.63 0.20 0.12 0.05 0.13
## [7] 0.06 0.88 0.05 0.52 0.04
## [1] -263330.28 0.63 0.20 0.12 0.05 0.12
## [7] 0.06 0.88 0.05 0.52 0.04
## [1] -263309.02 0.63 0.19 0.12 0.05 0.12
## [7] 0.05 0.89 0.05 0.52 0.05
## [1] -263286.73 0.63 0.19 0.12 0.06 0.12
## [7] 0.05 0.89 0.05 0.51 0.05
## [1] -263264.21 0.64 0.19 0.12 0.06 0.12
## [7] 0.05 0.89 0.05 0.51 0.05
## [1] -263242.66 0.64 0.18 0.12 0.06 0.11
## [7] 0.05 0.89 0.05 0.51 0.05
## [1] -263222.78 0.64 0.18 0.12 0.06 0.11
## [7] 0.04 0.89 0.05 0.51 0.05
## [1] -263205.56 0.64 0.18 0.11 0.07 0.11
## [7] 0.04 0.89 0.05 0.51 0.06
## [1] -263191.81 0.64 0.18 0.11 0.07 0.11
## [7] 0.04 0.89 0.04 0.51 0.06
## [1] -263182.23 0.64 0.17 0.11 0.07 0.10
## [7] 0.04 0.89 0.04 0.50 0.06
## [1] 24
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -267783.99 0.55 0.24 0.19 0.02 0.14
## [7] 0.08 0.88 0.04 0.51 0.05
## [1] -264335.74 0.59 0.22 0.17 0.02 0.15
## [7] 0.08 0.86 0.04 0.52 0.05
## [1] -263835.02 0.61 0.20 0.16 0.03 0.16
## [7] 0.09 0.86 0.05 0.53 0.05
## [1] -263676.17 0.62 0.19 0.16 0.03 0.16
## [7] 0.09 0.85 0.05 0.53 0.04
## [1] -263627.80 0.62 0.19 0.15 0.03 0.16
## [7] 0.08 0.85 0.05 0.53 0.04
## [1] -263621.63 0.63 0.18 0.15 0.04 0.16
## [7] 0.08 0.84 0.05 0.54 0.04
## [1] 25
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -267731.20 0.56 0.23 0.19 0.02 0.15
## [7] 0.09 0.88 0.04 0.51 0.05
## [1] -264708.30 0.61 0.20 0.16 0.03 0.17
## [7] 0.10 0.87 0.04 0.51 0.04
## [1] -264313.02 0.63 0.19 0.15 0.03 0.17
## [7] 0.10 0.86 0.04 0.51 0.04
## [1] -264195.99 0.64 0.18 0.14 0.04 0.18
## [7] 0.11 0.86 0.04 0.52 0.04
## [1] -264157.86 0.64 0.18 0.14 0.04 0.18
## [7] 0.11 0.85 0.05 0.52 0.04
## [1] -264144.75 0.64 0.17 0.14 0.04 0.19
## [7] 0.11 0.85 0.05 0.52 0.04
## [1] -264137.49 0.65 0.17 0.14 0.05 0.19
## [7] 0.11 0.85 0.05 0.52 0.04
## [1] 26
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -269373.79 0.57 0.23 0.18 0.02 0.16
## [7] 0.09 0.87 0.03 0.51 0.05
## [1] -264818.67 0.61 0.21 0.15 0.02 0.18
## [7] 0.09 0.86 0.04 0.51 0.05
## [1] -264208.75 0.63 0.20 0.14 0.03 0.19
## [7] 0.09 0.85 0.04 0.52 0.05
## [1] -264018.42 0.64 0.19 0.14 0.03 0.19
## [7] 0.09 0.85 0.04 0.52 0.05
## [1] -263950.31 0.64 0.19 0.13 0.04 0.20
## [7] 0.10 0.84 0.04 0.52 0.05
## [1] -263926.62 0.64 0.19 0.13 0.04 0.20
## [7] 0.10 0.84 0.04 0.53 0.05
## [1] -263920.06 0.64 0.19 0.13 0.04 0.20
## [7] 0.10 0.84 0.04 0.53 0.05
## [1] 27
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -269824.44 0.58 0.22 0.18 0.02 0.16
## [7] 0.08 0.87 0.03 0.51 0.05
## [1] -264468.03 0.61 0.20 0.16 0.02 0.18
## [7] 0.08 0.86 0.03 0.51 0.05
## [1] -263797.43 0.63 0.19 0.15 0.03 0.19
## [7] 0.08 0.85 0.04 0.52 0.05
## [1] -263601.03 0.64 0.19 0.15 0.03 0.20
## [7] 0.08 0.85 0.04 0.53 0.05
## [1] -263538.19 0.64 0.18 0.14 0.04 0.20
## [7] 0.09 0.84 0.04 0.53 0.05
## [1] -263523.40 0.64 0.18 0.14 0.04 0.21
## [7] 0.09 0.84 0.04 0.54 0.05
## [1] -263527.43 0.63 0.18 0.14 0.04 0.21
## [7] 0.09 0.84 0.04 0.54 0.05
## [1] 28
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -266204.55 0.54 0.29 0.15 0.02 0.13
## [7] 0.08 0.88 0.03 0.51 0.05
## [1] -263710.54 0.58 0.27 0.12 0.03 0.14
## [7] 0.08 0.87 0.04 0.51 0.04
## [1] -263504.80 0.60 0.26 0.10 0.03 0.14
## [7] 0.08 0.86 0.04 0.52 0.04
## [1] -263452.41 0.61 0.25 0.09 0.04 0.13
## [7] 0.08 0.86 0.04 0.52 0.04
## [1] -263434.00 0.62 0.25 0.09 0.05 0.13
## [7] 0.08 0.86 0.04 0.52 0.04
## [1] -263424.67 0.62 0.24 0.09 0.05 0.13
## [7] 0.07 0.86 0.04 0.53 0.04
## [1] 29
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -267788.65 0.56 0.25 0.17 0.02 0.14
## [7] 0.09 0.88 0.04 0.51 0.05
## [1] -264511.04 0.60 0.23 0.14 0.02 0.15
## [7] 0.09 0.87 0.04 0.51 0.05
## [1] -264073.57 0.62 0.22 0.13 0.03 0.16
## [7] 0.09 0.86 0.04 0.52 0.05
## [1] -263913.12 0.63 0.21 0.13 0.03 0.16
## [7] 0.09 0.85 0.05 0.52 0.04
## [1] -263840.55 0.63 0.21 0.12 0.04 0.16
## [7] 0.09 0.85 0.05 0.53 0.04
## [1] -263804.20 0.63 0.20 0.12 0.04 0.16
## [7] 0.09 0.84 0.05 0.53 0.04
## [1] -263783.55 0.63 0.20 0.12 0.04 0.16
## [7] 0.09 0.84 0.05 0.53 0.04
## [1] -263769.56 0.63 0.20 0.12 0.05 0.16
## [7] 0.09 0.84 0.05 0.53 0.04
## [1] -263757.04 0.63 0.20 0.12 0.05 0.16
## [7] 0.09 0.84 0.05 0.54 0.05
## [1] -263743.71 0.63 0.20 0.12 0.05 0.15
## [7] 0.09 0.84 0.05 0.54 0.05
## [1] -263728.47 0.63 0.20 0.12 0.05 0.15
## [7] 0.08 0.84 0.05 0.54 0.05
## [1] -263710.86 0.62 0.20 0.12 0.06 0.15
## [7] 0.08 0.84 0.05 0.54 0.05
## [1] -263690.79 0.62 0.20 0.12 0.06 0.15
## [7] 0.08 0.84 0.05 0.54 0.05
## [1] -263668.41 0.62 0.20 0.13 0.06 0.15
## [7] 0.08 0.84 0.05 0.54 0.05
## [1] -263643.98 0.61 0.20 0.13 0.06 0.15
## [7] 0.08 0.84 0.05 0.54 0.05
## [1] -263617.89 0.61 0.20 0.13 0.06 0.15
## [7] 0.08 0.84 0.05 0.54 0.05
## [1] -263590.56 0.61 0.20 0.13 0.07 0.15
## [7] 0.08 0.84 0.05 0.53 0.05
## [1] -263562.23 0.61 0.20 0.13 0.07 0.15
## [7] 0.08 0.84 0.05 0.53 0.05
## [1] -263533.44 0.60 0.20 0.13 0.07 0.15
## [7] 0.08 0.84 0.05 0.53 0.05
## [1] -263504.42 0.60 0.20 0.13 0.07 0.15
## [7] 0.08 0.84 0.05 0.53 0.06
## [1] -263475.53 0.60 0.20 0.13 0.08 0.15
## [7] 0.08 0.84 0.05 0.53 0.06
## [1] -263447.02 0.59 0.20 0.13 0.08 0.14
## [7] 0.08 0.84 0.05 0.53 0.06
## [1] -263419.08 0.59 0.20 0.13 0.08 0.14
## [7] 0.08 0.84 0.05 0.53 0.06
## [1] -263391.89 0.59 0.20 0.13 0.08 0.14
## [7] 0.08 0.84 0.05 0.53 0.06
## [1] -263365.59 0.58 0.20 0.13 0.08 0.14
## [7] 0.07 0.84 0.05 0.53 0.06
## [1] -263340.26 0.58 0.20 0.13 0.09 0.14
## [7] 0.07 0.84 0.05 0.52 0.06
## [1] -263315.98 0.58 0.20 0.13 0.09 0.14
## [7] 0.07 0.84 0.05 0.52 0.06
## [1] -263292.80 0.57 0.20 0.13 0.09 0.14
## [7] 0.07 0.84 0.05 0.52 0.06
## [1] -263270.74 0.57 0.20 0.14 0.09 0.14
## [7] 0.07 0.84 0.05 0.52 0.07
## [1] -263249.81 0.57 0.20 0.14 0.10 0.14
## [7] 0.07 0.84 0.05 0.52 0.07
## [1] -263230.01 0.56 0.20 0.14 0.10 0.14
## [7] 0.07 0.84 0.05 0.52 0.07
## [1] -263211.31 0.56 0.20 0.14 0.10 0.14
## [7] 0.07 0.84 0.05 0.52 0.07
## [1] -263193.70 0.55 0.20 0.14 0.10 0.14
## [7] 0.07 0.84 0.05 0.52 0.07
## [1] -263177.14 0.55 0.20 0.14 0.11 0.14
## [7] 0.07 0.84 0.05 0.51 0.07
## [1] -263161.61 0.55 0.20 0.14 0.11 0.14
## [7] 0.07 0.84 0.05 0.51 0.07
## [1] -263147.06 0.54 0.20 0.14 0.11 0.14
## [7] 0.07 0.84 0.05 0.51 0.07
## [1] -263133.46 0.54 0.20 0.14 0.12 0.14
## [7] 0.07 0.84 0.05 0.51 0.07
## [1] -263120.76 0.54 0.20 0.14 0.12 0.14
## [7] 0.07 0.84 0.05 0.51 0.08
## [1] -263108.94 0.53 0.20 0.14 0.12 0.14
## [7] 0.07 0.84 0.05 0.51 0.08
## [1] -263097.94 0.53 0.20 0.14 0.12 0.14
## [7] 0.07 0.84 0.05 0.51 0.08
## [1] -263087.74 0.52 0.21 0.15 0.13 0.13
## [7] 0.07 0.84 0.05 0.51 0.08
## [1] -263078.30 0.52 0.21 0.15 0.13 0.13
## [7] 0.07 0.84 0.05 0.51 0.08
## [1] 30
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -265331.09 0.54 0.19 0.25 0.02 0.15
## [7] 0.09 0.89 0.04 0.51 0.05
## [1] -263250.28 0.59 0.16 0.23 0.02 0.16
## [7] 0.10 0.88 0.04 0.52 0.04
## [1] -262967.28 0.61 0.14 0.22 0.03 0.17
## [7] 0.10 0.88 0.04 0.53 0.04
## [1] -262859.40 0.62 0.13 0.22 0.04 0.17
## [7] 0.10 0.88 0.04 0.54 0.04
## [1] -262808.62 0.62 0.12 0.22 0.04 0.17
## [7] 0.10 0.88 0.04 0.54 0.04
## [1] -262779.47 0.62 0.11 0.22 0.04 0.17
## [7] 0.10 0.88 0.04 0.55 0.04
## [1] -262758.20 0.63 0.11 0.22 0.05 0.17
## [7] 0.10 0.88 0.04 0.55 0.04
## [1] -262739.49 0.62 0.11 0.22 0.05 0.17
## [7] 0.10 0.88 0.04 0.55 0.04
## [1] -262722.20 0.62 0.10 0.22 0.06 0.16
## [7] 0.10 0.88 0.04 0.56 0.04
## [1] -262705.72 0.62 0.10 0.22 0.06 0.16
## [7] 0.10 0.88 0.04 0.56 0.04
## [1] -262690.48 0.62 0.10 0.22 0.06 0.16
## [7] 0.09 0.88 0.04 0.56 0.04
## [1] -262676.98 0.62 0.10 0.22 0.07 0.16
## [7] 0.09 0.88 0.04 0.56 0.04
## [1] -262665.76 0.62 0.10 0.22 0.07 0.15
## [7] 0.09 0.88 0.04 0.56 0.04
## [1] -262657.20 0.61 0.10 0.22 0.07 0.15
## [7] 0.08 0.88 0.04 0.57 0.04
ggplot(sampleinfo_organoid_notfetal, aes(as.numeric(as.character(passage.or.rescope.no_numeric)), thresholded_prior_ratio))+
geom_point(size=2,shape=21,color="black",aes(fill=as.factor(passage.or.rescope.no_numeric)))+xlab("Passage")+
ylab("Intermediate Peak Prior")+theme_bw()+theme(axis.title = element_text(size=12))+
#geom_text(aes(label=count, vjust=vjust, hjust=hjust), color="grey40", size=3)+
scale_x_continuous(breaks=c(1,2,3,4,6,7,8,2,4,10,11,14,16))+ scale_fill_manual(values=pass_col,name="Passage\nNumber", guide=F)
ggsave(here("figs","MTAB4957_mixture_model_ratio_maximize.pdf"), width=3, height=2)
sampleinfo_organoid_notfetal$thresholded_ratio_max<-F
sampleinfo_organoid_notfetal$thresholded_ratio_max[which(sampleinfo_organoid_notfetal$thresholded_prior_ratio>1)]<-T
percent_passing<-round((tapply(sampleinfo_organoid_notfetal$thresholded_ratio_max, sampleinfo_organoid_notfetal$passage.or.rescope.no_numeric, sum)/tapply(sampleinfo_organoid_notfetal$array.id, sampleinfo_organoid_notfetal$passage.or.rescope.no_numeric, length))*100,2)
passed_num<-tapply(sampleinfo_organoid_notfetal$thresholded_ratio_max, sampleinfo_organoid_notfetal$passage.or.rescope.no_numeric, sum)
org_numer<-tapply(sampleinfo_organoid_notfetal$array.id, sampleinfo_organoid_notfetal$passage.or.rescope.no_numeric, length)
df<-data.frame(passage=names(percent_passing), passing=percent_passing, pro_passing=percent_passing/100, count=org_numer, passed_num=passed_num)
df$passage.factor <- factor(df$passage, levels = c(11,9,8,6,4,3,2,1))
df<-cbind(df,(binom.confint(df$passed_num, df$count, method="exact", conf.level=0.95)))
df$upper<-df$upper*100
df$lower<-df$lower*100
print(df)
## passage passing pro_passing count passed_num passage.factor method x n
## 1 1 0 0.0 2 0 1 exact 0 2
## 2 2 0 0.0 6 0 2 exact 0 6
## 3 3 0 0.0 1 0 3 exact 0 1
## 4 4 0 0.0 5 0 4 exact 0 5
## 6 6 50 0.5 2 1 6 exact 1 2
## 8 8 0 0.0 2 0 8 exact 0 2
## 9 9 0 0.0 2 0 9 exact 0 2
## 11 11 50 0.5 10 5 11 exact 5 10
## mean lower upper
## 1 0.0 0.000000 84.18861
## 2 0.0 0.000000 45.92581
## 3 0.0 0.000000 97.50000
## 4 0.0 0.000000 52.18238
## 6 0.5 1.257912 98.74209
## 8 0.0 0.000000 84.18861
## 9 0.0 0.000000 84.18861
## 11 0.5 18.708603 81.29140
ggplot(df, aes(as.numeric(as.character(passage)), passing))+
geom_errorbar(aes(ymin=lower, ymax=upper), colour="grey70", width=.25)+
geom_line(color="grey20")+geom_point(size=1.25,shape=21,color="black",aes(fill=passage.factor))+xlab("Passage")+
ylab("Samples with Trimodal\nDistribution (%)")+theme_bw()+theme(axis.title = element_text(size=10))+
scale_x_continuous(breaks=c(1,2,3,4,6,7,8,2,4,10,11,14,16))+ scale_fill_manual(values=pass_col,name="Passage\nNumber", guide=F)
ggsave(here("figs","MTAB4957_mixture_model_ratio_threshold_maximize.pdf"), width=3, height=2)
## plot all samples
plts_paired<-lapply(1:nrow(sampleinfo_organoid_notfetal), function(x){
print(x)
passage<-paste("passage: ",sampleinfo_organoid_notfetal$passage.or.rescope.no_numeric[x],"\nIndividual: ", sampleinfo_organoid_notfetal$Characteristics.individual.[x],"\nRatio I/H: " ,round(sampleinfo_organoid_notfetal$thresholded_prior_ratio[x],2), sep="")
converted<-as.numeric(round(MTAB4957_beta_VeryVariable[,x]*1000,0))
counts<-rep(1000, length(converted))
res = em(converted, counts, .41, .31, .27, 0.01, .1, .1, .90, .03, .5, .05)
draw_fit_params_gg(converted, counts, res,passage)
})
## [1] 1
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -270103.38 0.60 0.23 0.15 0.02 0.16
## [7] 0.09 0.87 0.04 0.51 0.05
## [1] -265610.50 0.65 0.20 0.12 0.03 0.18
## [7] 0.10 0.85 0.04 0.51 0.04
## [1] -264849.45 0.66 0.19 0.11 0.04 0.20
## [7] 0.11 0.84 0.04 0.52 0.04
## [1] -264579.20 0.67 0.18 0.10 0.04 0.21
## [7] 0.11 0.83 0.04 0.52 0.04
## [1] -264483.85 0.67 0.18 0.10 0.05 0.21
## [7] 0.12 0.83 0.04 0.52 0.04
## [1] -264462.54 0.67 0.18 0.10 0.05 0.22
## [7] 0.12 0.82 0.05 0.53 0.04
## [1] -264472.22 0.67 0.18 0.10 0.06 0.22
## [7] 0.12 0.82 0.05 0.53 0.04
## [1] 2
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -267948.50 0.57 0.28 0.12 0.02 0.14
## [7] 0.09 0.87 0.04 0.50 0.05
## [1] -265150.42 0.62 0.26 0.09 0.03 0.15
## [7] 0.10 0.85 0.04 0.51 0.04
## [1] -264649.49 0.64 0.25 0.08 0.04 0.15
## [7] 0.11 0.84 0.05 0.51 0.04
## [1] -264426.43 0.64 0.24 0.07 0.04 0.16
## [7] 0.11 0.83 0.05 0.51 0.04
## [1] -264304.19 0.65 0.24 0.07 0.05 0.16
## [7] 0.11 0.82 0.05 0.51 0.04
## [1] -264228.23 0.65 0.24 0.06 0.05 0.16
## [7] 0.11 0.82 0.05 0.51 0.04
## [1] -264174.45 0.64 0.24 0.06 0.06 0.16
## [7] 0.11 0.81 0.05 0.51 0.04
## [1] -264131.03 0.64 0.23 0.06 0.06 0.16
## [7] 0.11 0.81 0.05 0.51 0.04
## [1] -264091.61 0.64 0.23 0.06 0.07 0.16
## [7] 0.11 0.80 0.06 0.51 0.04
## [1] -264052.64 0.63 0.23 0.06 0.07 0.16
## [7] 0.11 0.80 0.06 0.51 0.04
## [1] -264012.18 0.63 0.23 0.06 0.08 0.15
## [7] 0.11 0.80 0.06 0.51 0.04
## [1] -263969.23 0.63 0.23 0.06 0.08 0.15
## [7] 0.10 0.79 0.06 0.51 0.04
## [1] -263923.51 0.62 0.23 0.06 0.08 0.15
## [7] 0.10 0.79 0.06 0.51 0.04
## [1] -263875.00 0.62 0.23 0.06 0.09 0.15
## [7] 0.10 0.79 0.06 0.51 0.05
## [1] -263824.06 0.61 0.23 0.06 0.09 0.15
## [7] 0.10 0.79 0.06 0.51 0.05
## [1] -263771.15 0.61 0.23 0.06 0.09 0.15
## [7] 0.10 0.79 0.06 0.51 0.05
## [1] -263716.82 0.61 0.23 0.06 0.10 0.15
## [7] 0.10 0.79 0.06 0.51 0.05
## [1] -263661.61 0.60 0.23 0.07 0.10 0.14
## [7] 0.10 0.79 0.06 0.50 0.05
## [1] -263606.08 0.60 0.23 0.07 0.10 0.14
## [7] 0.09 0.79 0.06 0.50 0.05
## [1] -263550.73 0.59 0.23 0.07 0.11 0.14
## [7] 0.09 0.79 0.06 0.50 0.05
## [1] -263496.13 0.59 0.23 0.07 0.11 0.14
## [7] 0.09 0.79 0.06 0.50 0.05
## [1] -263442.33 0.59 0.23 0.07 0.11 0.14
## [7] 0.09 0.79 0.06 0.50 0.06
## [1] -263389.84 0.58 0.23 0.07 0.12 0.14
## [7] 0.09 0.79 0.06 0.50 0.06
## [1] -263338.89 0.58 0.23 0.07 0.12 0.13
## [7] 0.09 0.79 0.06 0.49 0.06
## [1] -263289.68 0.57 0.23 0.07 0.12 0.13
## [7] 0.09 0.79 0.06 0.49 0.06
## [1] -263242.36 0.57 0.23 0.07 0.13 0.13
## [7] 0.08 0.79 0.06 0.49 0.06
## [1] -263197.03 0.57 0.23 0.08 0.13 0.13
## [7] 0.08 0.79 0.06 0.49 0.06
## [1] -263153.75 0.56 0.23 0.08 0.13 0.13
## [7] 0.08 0.79 0.06 0.49 0.06
## [1] -263112.73 0.56 0.23 0.08 0.14 0.13
## [7] 0.08 0.79 0.06 0.48 0.06
## [1] -263073.78 0.55 0.23 0.08 0.14 0.13
## [7] 0.08 0.79 0.06 0.48 0.06
## [1] -263036.82 0.55 0.22 0.08 0.14 0.12
## [7] 0.08 0.79 0.06 0.48 0.07
## [1] -263002.04 0.55 0.22 0.08 0.15 0.12
## [7] 0.08 0.79 0.06 0.48 0.07
## [1] -262969.40 0.54 0.22 0.08 0.15 0.12
## [7] 0.07 0.79 0.06 0.47 0.07
## [1] -262938.87 0.54 0.22 0.08 0.16 0.12
## [7] 0.07 0.79 0.07 0.47 0.07
## [1] -262910.43 0.53 0.22 0.09 0.16 0.12
## [7] 0.07 0.79 0.07 0.47 0.07
## [1] -262884.05 0.53 0.22 0.09 0.16 0.12
## [7] 0.07 0.79 0.07 0.47 0.07
## [1] -262859.71 0.53 0.22 0.09 0.17 0.11
## [7] 0.07 0.79 0.07 0.47 0.07
## [1] -262837.35 0.52 0.22 0.09 0.17 0.11
## [7] 0.07 0.79 0.07 0.46 0.07
## [1] -262816.93 0.52 0.22 0.09 0.17 0.11
## [7] 0.06 0.79 0.07 0.46 0.07
## [1] -262798.47 0.51 0.22 0.09 0.18 0.11
## [7] 0.06 0.79 0.07 0.46 0.08
## [1] -262782.05 0.51 0.22 0.09 0.18 0.11
## [7] 0.06 0.79 0.07 0.46 0.08
## [1] -262767.53 0.50 0.21 0.10 0.19 0.11
## [7] 0.06 0.79 0.07 0.46 0.08
## [1] -262754.77 0.50 0.21 0.10 0.19 0.11
## [7] 0.06 0.79 0.07 0.45 0.08
## [1] -262743.78 0.50 0.21 0.10 0.19 0.10
## [7] 0.06 0.79 0.07 0.45 0.08
## [1] -262734.60 0.49 0.21 0.10 0.20 0.10
## [7] 0.06 0.79 0.07 0.45 0.08
## [1] 3
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -265933.53 0.55 0.26 0.16 0.02 0.14
## [7] 0.08 0.89 0.04 0.51 0.04
## [1] -263730.92 0.60 0.24 0.13 0.03 0.14
## [7] 0.08 0.88 0.05 0.51 0.04
## [1] -263609.69 0.62 0.23 0.12 0.04 0.14
## [7] 0.07 0.88 0.05 0.51 0.04
## [1] -263566.97 0.64 0.21 0.11 0.04 0.13
## [7] 0.07 0.88 0.05 0.51 0.04
## [1] -263529.40 0.64 0.20 0.10 0.05 0.13
## [7] 0.06 0.88 0.05 0.51 0.04
## [1] -263491.42 0.65 0.20 0.10 0.06 0.12
## [7] 0.06 0.88 0.05 0.51 0.04
## [1] -263454.75 0.65 0.19 0.09 0.07 0.12
## [7] 0.05 0.88 0.05 0.51 0.04
## [1] -263426.41 0.65 0.19 0.09 0.07 0.11
## [7] 0.04 0.88 0.05 0.51 0.04
## [1] -263411.13 0.65 0.18 0.09 0.08 0.10
## [7] 0.04 0.88 0.05 0.51 0.04
## [1] -263413.40 0.65 0.18 0.09 0.08 0.10
## [7] 0.03 0.88 0.04 0.51 0.04
## [1] 4
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -268327.69 0.57 0.27 0.13 0.02 0.14
## [7] 0.08 0.88 0.04 0.50 0.05
## [1] -265055.63 0.62 0.26 0.10 0.03 0.15
## [7] 0.09 0.86 0.05 0.51 0.04
## [1] -264657.68 0.64 0.25 0.08 0.04 0.16
## [7] 0.09 0.85 0.05 0.51 0.04
## [1] -264483.42 0.64 0.24 0.07 0.04 0.16
## [7] 0.09 0.85 0.05 0.51 0.04
## [1] -264375.78 0.65 0.23 0.07 0.05 0.16
## [7] 0.09 0.84 0.06 0.51 0.04
## [1] -264295.85 0.65 0.23 0.06 0.06 0.16
## [7] 0.09 0.83 0.06 0.51 0.04
## [1] -264228.76 0.65 0.23 0.06 0.06 0.16
## [7] 0.09 0.83 0.06 0.51 0.04
## [1] -264167.37 0.65 0.23 0.06 0.07 0.16
## [7] 0.09 0.83 0.06 0.51 0.04
## [1] -264108.90 0.64 0.23 0.06 0.07 0.16
## [7] 0.09 0.82 0.06 0.51 0.04
## [1] -264051.78 0.64 0.23 0.06 0.07 0.16
## [7] 0.09 0.82 0.06 0.51 0.04
## [1] -263995.16 0.64 0.23 0.06 0.08 0.16
## [7] 0.09 0.82 0.06 0.51 0.04
## [1] -263938.68 0.64 0.22 0.06 0.08 0.15
## [7] 0.08 0.82 0.06 0.51 0.04
## [1] -263882.45 0.63 0.22 0.06 0.08 0.15
## [7] 0.08 0.82 0.07 0.51 0.04
## [1] -263826.28 0.63 0.22 0.06 0.09 0.15
## [7] 0.08 0.81 0.07 0.51 0.05
## [1] -263770.51 0.63 0.22 0.06 0.09 0.15
## [7] 0.08 0.81 0.07 0.51 0.05
## [1] -263715.49 0.62 0.22 0.06 0.09 0.15
## [7] 0.08 0.81 0.07 0.51 0.05
## [1] -263661.54 0.62 0.22 0.06 0.10 0.15
## [7] 0.08 0.81 0.07 0.51 0.05
## [1] -263609.02 0.62 0.22 0.06 0.10 0.15
## [7] 0.08 0.81 0.07 0.51 0.05
## [1] -263558.22 0.61 0.22 0.06 0.10 0.14
## [7] 0.07 0.81 0.07 0.50 0.05
## [1] -263509.50 0.61 0.22 0.06 0.11 0.14
## [7] 0.07 0.81 0.07 0.50 0.05
## [1] -263462.88 0.61 0.22 0.06 0.11 0.14
## [7] 0.07 0.81 0.07 0.50 0.05
## [1] -263418.64 0.60 0.22 0.07 0.11 0.14
## [7] 0.07 0.81 0.07 0.50 0.06
## [1] -263376.90 0.60 0.22 0.07 0.12 0.14
## [7] 0.07 0.81 0.07 0.50 0.06
## [1] -263337.76 0.59 0.22 0.07 0.12 0.14
## [7] 0.07 0.81 0.07 0.49 0.06
## [1] -263301.26 0.59 0.22 0.07 0.13 0.13
## [7] 0.07 0.81 0.07 0.49 0.06
## [1] -263267.41 0.59 0.22 0.07 0.13 0.13
## [7] 0.06 0.81 0.07 0.49 0.06
## [1] -263236.20 0.58 0.21 0.07 0.13 0.13
## [7] 0.06 0.81 0.07 0.49 0.06
## [1] -263207.60 0.58 0.21 0.07 0.14 0.13
## [7] 0.06 0.81 0.07 0.49 0.06
## [1] -263181.58 0.58 0.21 0.07 0.14 0.13
## [7] 0.06 0.81 0.07 0.48 0.07
## [1] -263158.07 0.57 0.21 0.07 0.14 0.13
## [7] 0.06 0.81 0.07 0.48 0.07
## [1] -263137.02 0.57 0.21 0.07 0.15 0.13
## [7] 0.06 0.81 0.07 0.48 0.07
## [1] -263118.37 0.56 0.21 0.08 0.15 0.12
## [7] 0.06 0.81 0.07 0.48 0.07
## [1] -263102.03 0.56 0.21 0.08 0.15 0.12
## [7] 0.06 0.81 0.07 0.48 0.07
## [1] -263087.93 0.56 0.21 0.08 0.16 0.12
## [7] 0.05 0.81 0.07 0.47 0.07
## [1] -263076.02 0.55 0.21 0.08 0.16 0.12
## [7] 0.05 0.81 0.07 0.47 0.07
## [1] -263066.20 0.55 0.21 0.08 0.17 0.12
## [7] 0.05 0.81 0.07 0.47 0.07
## [1] 5
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -263896.17 0.53 0.28 0.17 0.02 0.13
## [7] 0.08 0.89 0.03 0.51 0.04
## [1] -262305.00 0.57 0.26 0.15 0.03 0.13
## [7] 0.08 0.88 0.03 0.51 0.04
## [1] -262396.01 0.59 0.25 0.13 0.04 0.13
## [7] 0.08 0.88 0.03 0.52 0.03
## [1] -262563.43 0.60 0.24 0.12 0.04 0.12
## [7] 0.07 0.88 0.03 0.52 0.03
## [1] -262741.61 0.60 0.23 0.12 0.05 0.12
## [7] 0.07 0.89 0.03 0.52 0.03
## [1] -262910.45 0.60 0.23 0.11 0.06 0.12
## [7] 0.06 0.89 0.03 0.52 0.03
## [1] -263061.11 0.60 0.22 0.11 0.07 0.11
## [7] 0.06 0.89 0.03 0.52 0.03
## [1] -263187.95 0.60 0.22 0.11 0.07 0.11
## [7] 0.05 0.89 0.02 0.52 0.03
## [1] -263288.70 0.60 0.21 0.11 0.08 0.11
## [7] 0.05 0.89 0.02 0.52 0.03
## [1] -263365.51 0.60 0.21 0.11 0.08 0.10
## [7] 0.05 0.89 0.02 0.52 0.03
## [1] -263418.72 0.60 0.21 0.11 0.08 0.10
## [7] 0.05 0.89 0.02 0.52 0.03
## [1] -263453.60 0.60 0.21 0.11 0.09 0.10
## [7] 0.04 0.89 0.02 0.52 0.03
## [1] -263473.93 0.60 0.21 0.11 0.09 0.10
## [7] 0.04 0.90 0.02 0.52 0.03
## [1] -263482.87 0.60 0.20 0.10 0.09 0.09
## [7] 0.04 0.90 0.02 0.52 0.03
## [1] 6
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -262708.15 0.52 0.31 0.15 0.02 0.12
## [7] 0.08 0.89 0.03 0.51 0.04
## [1] -261310.86 0.55 0.30 0.12 0.03 0.11
## [7] 0.07 0.89 0.03 0.51 0.03
## [1] -261345.87 0.57 0.29 0.10 0.04 0.11
## [7] 0.06 0.89 0.03 0.51 0.03
## [1] -261458.68 0.58 0.28 0.09 0.05 0.10
## [7] 0.05 0.89 0.03 0.51 0.03
## [1] -261604.18 0.59 0.27 0.09 0.06 0.09
## [7] 0.04 0.90 0.03 0.51 0.03
## [1] -261760.99 0.59 0.26 0.08 0.07 0.09
## [7] 0.04 0.90 0.02 0.51 0.03
## [1] -261915.76 0.59 0.25 0.08 0.07 0.08
## [7] 0.03 0.90 0.02 0.51 0.03
## [1] -262059.79 0.60 0.25 0.08 0.08 0.08
## [7] 0.03 0.90 0.02 0.51 0.03
## [1] -262188.71 0.60 0.24 0.08 0.08 0.08
## [7] 0.02 0.91 0.02 0.51 0.03
## [1] -262301.69 0.60 0.24 0.07 0.09 0.07
## [7] 0.02 0.91 0.02 0.51 0.03
## [1] -262398.35 0.60 0.24 0.07 0.09 0.07
## [7] 0.02 0.91 0.02 0.51 0.03
## [1] -262478.14 0.60 0.23 0.07 0.09 0.07
## [7] 0.02 0.91 0.02 0.51 0.03
## [1] -262540.98 0.61 0.23 0.07 0.09 0.07
## [7] 0.02 0.91 0.01 0.51 0.04
## [1] -262587.79 0.61 0.23 0.07 0.10 0.07
## [7] 0.02 0.91 0.01 0.51 0.04
## [1] -262620.34 0.61 0.23 0.07 0.10 0.07
## [7] 0.02 0.91 0.01 0.50 0.04
## [1] -262640.65 0.61 0.22 0.07 0.10 0.07
## [7] 0.02 0.91 0.01 0.50 0.04
## [1] -262650.63 0.61 0.22 0.07 0.10 0.07
## [7] 0.02 0.91 0.01 0.50 0.04
## [1] 7
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -266156.99 0.55 0.23 0.20 0.02 0.14
## [7] 0.09 0.89 0.04 0.51 0.05
## [1] -263918.14 0.60 0.20 0.17 0.03 0.15
## [7] 0.09 0.88 0.04 0.52 0.04
## [1] -263719.46 0.62 0.19 0.16 0.03 0.16
## [7] 0.09 0.88 0.04 0.52 0.04
## [1] -263668.00 0.63 0.18 0.15 0.04 0.16
## [7] 0.09 0.87 0.04 0.53 0.04
## [1] -263651.32 0.64 0.17 0.15 0.04 0.16
## [7] 0.09 0.87 0.04 0.53 0.04
## [1] -263643.44 0.64 0.16 0.15 0.05 0.15
## [7] 0.09 0.87 0.04 0.54 0.04
## [1] 8
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -269727.89 0.59 0.24 0.15 0.02 0.16
## [7] 0.09 0.87 0.04 0.50 0.05
## [1] -265787.44 0.64 0.22 0.11 0.03 0.17
## [7] 0.10 0.86 0.05 0.51 0.04
## [1] -265125.41 0.66 0.21 0.10 0.04 0.19
## [7] 0.10 0.85 0.05 0.51 0.04
## [1] -264875.78 0.67 0.20 0.09 0.04 0.19
## [7] 0.11 0.84 0.05 0.52 0.04
## [1] -264777.19 0.67 0.20 0.09 0.05 0.20
## [7] 0.11 0.83 0.06 0.52 0.04
## [1] -264745.47 0.67 0.20 0.09 0.05 0.20
## [7] 0.11 0.82 0.06 0.52 0.04
## [1] -264743.71 0.67 0.19 0.08 0.05 0.21
## [7] 0.12 0.82 0.06 0.52 0.04
## [1] 9
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -269947.47 0.59 0.23 0.16 0.02 0.16
## [7] 0.09 0.87 0.03 0.51 0.05
## [1] -264782.87 0.63 0.20 0.14 0.03 0.17
## [7] 0.09 0.85 0.03 0.52 0.04
## [1] -264002.79 0.65 0.18 0.13 0.03 0.18
## [7] 0.09 0.84 0.04 0.53 0.04
## [1] -263744.75 0.66 0.17 0.13 0.04 0.19
## [7] 0.10 0.83 0.04 0.53 0.04
## [1] -263658.77 0.66 0.17 0.13 0.05 0.19
## [7] 0.10 0.83 0.04 0.54 0.04
## [1] -263640.91 0.66 0.17 0.13 0.05 0.19
## [7] 0.10 0.82 0.04 0.54 0.04
## [1] -263649.12 0.65 0.16 0.13 0.06 0.19
## [7] 0.10 0.82 0.04 0.54 0.04
## [1] 10
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -269866.23 0.59 0.25 0.14 0.02 0.15
## [7] 0.09 0.86 0.03 0.51 0.05
## [1] -265019.48 0.63 0.22 0.11 0.03 0.17
## [7] 0.09 0.85 0.04 0.51 0.04
## [1] -264281.88 0.65 0.21 0.10 0.04 0.17
## [7] 0.09 0.83 0.04 0.52 0.04
## [1] -264016.70 0.66 0.20 0.10 0.04 0.18
## [7] 0.10 0.83 0.04 0.52 0.04
## [1] -263913.05 0.66 0.20 0.10 0.05 0.18
## [7] 0.10 0.82 0.04 0.53 0.04
## [1] -263876.53 0.66 0.19 0.10 0.06 0.18
## [7] 0.10 0.81 0.04 0.53 0.04
## [1] -263867.28 0.65 0.19 0.10 0.06 0.18
## [7] 0.10 0.81 0.04 0.53 0.04
## [1] 11
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -269220.74 0.58 0.24 0.16 0.02 0.15
## [7] 0.09 0.86 0.03 0.51 0.05
## [1] -264457.82 0.62 0.22 0.13 0.03 0.16
## [7] 0.09 0.85 0.03 0.52 0.04
## [1] -263816.32 0.64 0.20 0.12 0.03 0.17
## [7] 0.09 0.84 0.03 0.52 0.04
## [1] -263619.25 0.64 0.20 0.12 0.04 0.17
## [7] 0.09 0.83 0.03 0.53 0.04
## [1] -263555.15 0.64 0.19 0.12 0.05 0.17
## [7] 0.09 0.83 0.04 0.53 0.04
## [1] -263537.61 0.64 0.19 0.12 0.05 0.17
## [7] 0.09 0.82 0.04 0.53 0.04
## [1] -263535.21 0.64 0.19 0.12 0.06 0.17
## [7] 0.09 0.82 0.04 0.53 0.04
## [1] 12
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -269547.80 0.58 0.26 0.14 0.02 0.14
## [7] 0.09 0.86 0.03 0.51 0.05
## [1] -264712.75 0.62 0.24 0.11 0.03 0.16
## [7] 0.09 0.84 0.03 0.52 0.04
## [1] -263961.59 0.64 0.22 0.10 0.04 0.16
## [7] 0.09 0.83 0.03 0.52 0.04
## [1] -263706.98 0.65 0.22 0.10 0.04 0.16
## [7] 0.09 0.82 0.04 0.53 0.04
## [1] -263619.22 0.65 0.21 0.09 0.05 0.16
## [7] 0.09 0.81 0.04 0.53 0.04
## [1] -263597.40 0.64 0.21 0.09 0.05 0.16
## [7] 0.09 0.81 0.04 0.53 0.04
## [1] -263600.38 0.64 0.21 0.09 0.06 0.16
## [7] 0.09 0.80 0.04 0.53 0.04
## [1] 13
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -259769.23 0.48 0.32 0.18 0.02 0.11
## [7] 0.07 0.90 0.03 0.51 0.03
## [1] -258078.74 0.50 0.31 0.16 0.03 0.10
## [7] 0.05 0.90 0.03 0.52 0.03
## [1] -257929.05 0.51 0.30 0.14 0.04 0.10
## [7] 0.05 0.90 0.03 0.53 0.02
## [1] -258104.90 0.52 0.30 0.14 0.05 0.09
## [7] 0.04 0.91 0.03 0.53 0.02
## [1] -258378.48 0.51 0.29 0.13 0.06 0.09
## [7] 0.04 0.91 0.02 0.53 0.02
## [1] -258619.09 0.51 0.29 0.13 0.07 0.08
## [7] 0.03 0.91 0.02 0.53 0.01
## [1] -258783.69 0.50 0.28 0.13 0.08 0.08
## [7] 0.03 0.91 0.02 0.53 0.01
## [1] -258876.56 0.50 0.28 0.13 0.09 0.08
## [7] 0.03 0.91 0.02 0.53 0.02
## [1] -258911.89 0.49 0.28 0.13 0.09 0.08
## [7] 0.03 0.91 0.02 0.53 0.02
## [1] -258909.71 0.49 0.28 0.13 0.10 0.08
## [7] 0.03 0.91 0.02 0.53 0.02
## [1] 14
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -259752.33 0.48 0.30 0.21 0.02 0.11
## [7] 0.07 0.90 0.03 0.52 0.04
## [1] -257997.02 0.50 0.29 0.19 0.02 0.11
## [7] 0.05 0.90 0.03 0.53 0.03
## [1] -257877.11 0.51 0.28 0.18 0.03 0.10
## [7] 0.05 0.91 0.03 0.53 0.02
## [1] -258059.72 0.52 0.27 0.17 0.05 0.10
## [7] 0.04 0.91 0.02 0.54 0.02
## [1] -258347.34 0.52 0.26 0.17 0.06 0.09
## [7] 0.03 0.91 0.02 0.54 0.02
## [1] -258622.45 0.51 0.26 0.16 0.07 0.09
## [7] 0.03 0.91 0.02 0.54 0.02
## [1] -258836.89 0.51 0.25 0.16 0.07 0.09
## [7] 0.03 0.91 0.02 0.54 0.01
## [1] -258972.88 0.51 0.25 0.16 0.08 0.09
## [7] 0.03 0.91 0.02 0.54 0.01
## [1] -259051.97 0.50 0.25 0.16 0.08 0.08
## [7] 0.03 0.91 0.02 0.54 0.01
## [1] -259083.13 0.50 0.25 0.16 0.09 0.08
## [7] 0.03 0.91 0.02 0.54 0.02
## [1] -259088.87 0.50 0.25 0.16 0.09 0.08
## [7] 0.03 0.91 0.02 0.55 0.02
## [1] 15
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -259682.08 0.48 0.32 0.19 0.02 0.11
## [7] 0.06 0.90 0.03 0.52 0.03
## [1] -257554.74 0.50 0.31 0.16 0.03 0.10
## [7] 0.05 0.90 0.03 0.53 0.03
## [1] -257281.93 0.51 0.31 0.15 0.04 0.09
## [7] 0.04 0.91 0.03 0.53 0.02
## [1] -257424.24 0.51 0.30 0.14 0.05 0.09
## [7] 0.03 0.91 0.03 0.54 0.02
## [1] -257696.08 0.51 0.29 0.14 0.06 0.09
## [7] 0.03 0.91 0.02 0.54 0.02
## [1] -257947.97 0.50 0.29 0.14 0.07 0.08
## [7] 0.03 0.91 0.02 0.54 0.01
## [1] -258121.06 0.49 0.29 0.14 0.08 0.08
## [7] 0.03 0.91 0.02 0.54 0.01
## [1] -258214.98 0.49 0.28 0.14 0.09 0.08
## [7] 0.03 0.91 0.02 0.54 0.01
## [1] -258247.70 0.49 0.28 0.14 0.09 0.08
## [7] 0.03 0.91 0.02 0.54 0.01
## [1] -258245.26 0.48 0.28 0.14 0.10 0.08
## [7] 0.03 0.91 0.02 0.55 0.01
## [1] 16
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -267714.39 0.56 0.23 0.20 0.02 0.16
## [7] 0.08 0.89 0.04 0.51 0.05
## [1] -263840.55 0.59 0.21 0.17 0.02 0.17
## [7] 0.07 0.88 0.04 0.52 0.04
## [1] -263510.94 0.61 0.20 0.16 0.03 0.17
## [7] 0.07 0.88 0.04 0.53 0.04
## [1] -263426.83 0.62 0.19 0.15 0.04 0.17
## [7] 0.07 0.87 0.05 0.53 0.04
## [1] -263404.13 0.63 0.18 0.15 0.04 0.17
## [7] 0.07 0.87 0.05 0.54 0.04
## [1] -263402.99 0.63 0.18 0.15 0.04 0.17
## [7] 0.07 0.87 0.05 0.54 0.04
## [1] 17
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -253828.02 0.42 0.34 0.22 0.01 0.09
## [7] 0.05 0.92 0.03 0.53 0.03
## [1] -249506.73 0.43 0.35 0.21 0.02 0.07
## [7] 0.03 0.93 0.02 0.54 0.02
## [1] -247643.30 0.42 0.34 0.20 0.04 0.06
## [7] 0.02 0.93 0.02 0.54 0.02
## [1] -247096.75 0.42 0.33 0.20 0.05 0.06
## [7] 0.02 0.93 0.01 0.55 0.01
## [1] -247104.69 0.41 0.33 0.19 0.07 0.06
## [7] 0.02 0.93 0.01 0.55 0.01
## [1] 18
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -268311.76 0.56 0.26 0.16 0.02 0.14
## [7] 0.08 0.87 0.04 0.51 0.05
## [1] -264655.97 0.60 0.24 0.13 0.03 0.15
## [7] 0.08 0.86 0.05 0.52 0.05
## [1] -264080.51 0.62 0.23 0.12 0.03 0.15
## [7] 0.08 0.85 0.05 0.52 0.04
## [1] -263871.65 0.63 0.22 0.11 0.04 0.15
## [7] 0.08 0.84 0.05 0.53 0.04
## [1] -263795.56 0.64 0.21 0.11 0.04 0.15
## [7] 0.08 0.83 0.05 0.53 0.04
## [1] -263775.52 0.64 0.21 0.11 0.04 0.15
## [7] 0.08 0.83 0.05 0.53 0.04
## [1] -263777.36 0.64 0.20 0.11 0.05 0.15
## [7] 0.08 0.82 0.06 0.53 0.04
## [1] 19
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -254974.48 0.43 0.34 0.22 0.01 0.09
## [7] 0.05 0.92 0.03 0.53 0.03
## [1] -250206.20 0.43 0.34 0.21 0.02 0.08
## [7] 0.03 0.93 0.02 0.54 0.02
## [1] -248591.60 0.43 0.34 0.20 0.03 0.07
## [7] 0.02 0.93 0.02 0.55 0.01
## [1] -248222.35 0.42 0.33 0.20 0.05 0.07
## [7] 0.02 0.93 0.02 0.55 0.01
## [1] -248282.61 0.41 0.33 0.19 0.07 0.07
## [7] 0.02 0.94 0.01 0.56 0.01
## [1] -248417.01 0.40 0.32 0.19 0.08 0.06
## [7] 0.02 0.94 0.01 0.56 0.01
## [1] -248490.51 0.40 0.32 0.19 0.09 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248504.56 0.39 0.32 0.19 0.09 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248483.83 0.39 0.32 0.19 0.09 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248447.40 0.39 0.32 0.20 0.10 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248407.71 0.39 0.32 0.20 0.10 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248374.19 0.38 0.32 0.20 0.10 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248340.00 0.38 0.32 0.20 0.10 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248309.41 0.38 0.32 0.20 0.10 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248282.71 0.38 0.32 0.20 0.10 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248259.42 0.38 0.32 0.20 0.10 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248239.13 0.38 0.32 0.20 0.10 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248221.50 0.38 0.32 0.20 0.10 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248206.19 0.38 0.32 0.20 0.10 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248192.91 0.37 0.32 0.20 0.10 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248181.34 0.37 0.32 0.20 0.10 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248171.27 0.37 0.32 0.20 0.11 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] -248166.53 0.37 0.32 0.20 0.11 0.06
## [7] 0.01 0.94 0.01 0.56 0.01
## [1] 20
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -268423.74 0.56 0.26 0.16 0.02 0.15
## [7] 0.08 0.88 0.04 0.51 0.05
## [1] -264539.44 0.60 0.24 0.14 0.02 0.15
## [7] 0.08 0.86 0.05 0.51 0.05
## [1] -264042.09 0.62 0.23 0.13 0.03 0.16
## [7] 0.08 0.85 0.05 0.52 0.04
## [1] -263869.42 0.63 0.22 0.12 0.03 0.16
## [7] 0.08 0.85 0.05 0.52 0.04
## [1] -263802.11 0.63 0.22 0.12 0.04 0.16
## [7] 0.08 0.84 0.05 0.53 0.04
## [1] -263777.83 0.63 0.21 0.12 0.04 0.16
## [7] 0.07 0.84 0.06 0.53 0.04
## [1] -263770.78 0.63 0.21 0.11 0.04 0.15
## [7] 0.07 0.83 0.06 0.53 0.04
## [1] 21
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -269112.94 0.57 0.19 0.22 0.02 0.19
## [7] 0.06 0.90 0.04 0.50 0.05
## [1] -262778.77 0.60 0.18 0.19 0.02 0.21
## [7] 0.06 0.90 0.05 0.51 0.04
## [1] -262363.69 0.61 0.18 0.18 0.03 0.21
## [7] 0.05 0.90 0.05 0.52 0.04
## [1] -262336.88 0.62 0.17 0.17 0.04 0.22
## [7] 0.05 0.90 0.05 0.52 0.04
## [1] -262368.78 0.62 0.17 0.17 0.04 0.22
## [7] 0.05 0.90 0.05 0.53 0.04
## [1] -262403.04 0.62 0.17 0.17 0.05 0.22
## [7] 0.05 0.90 0.05 0.53 0.04
## [1] -262427.84 0.61 0.17 0.17 0.05 0.22
## [7] 0.05 0.90 0.04 0.53 0.04
## [1] -262440.14 0.61 0.17 0.16 0.06 0.22
## [7] 0.04 0.90 0.04 0.54 0.04
## [1] -262439.94 0.61 0.17 0.16 0.06 0.22
## [7] 0.04 0.90 0.04 0.54 0.04
## [1] 22
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -268870.79 0.57 0.22 0.20 0.02 0.15
## [7] 0.08 0.88 0.04 0.51 0.05
## [1] -264530.76 0.61 0.19 0.17 0.02 0.17
## [7] 0.08 0.86 0.04 0.52 0.05
## [1] -263860.41 0.63 0.18 0.17 0.03 0.17
## [7] 0.08 0.85 0.04 0.53 0.05
## [1] -263641.49 0.63 0.17 0.16 0.03 0.18
## [7] 0.08 0.85 0.05 0.54 0.04
## [1] -263574.84 0.64 0.16 0.16 0.04 0.18
## [7] 0.08 0.84 0.05 0.54 0.04
## [1] -263567.63 0.64 0.16 0.16 0.04 0.18
## [7] 0.08 0.84 0.05 0.55 0.04
## [1] 23
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -266085.21 0.54 0.26 0.18 0.02 0.14
## [7] 0.08 0.89 0.04 0.51 0.05
## [1] -263573.37 0.58 0.24 0.16 0.02 0.14
## [7] 0.08 0.89 0.05 0.51 0.04
## [1] -263440.72 0.60 0.23 0.14 0.03 0.14
## [7] 0.07 0.88 0.05 0.51 0.04
## [1] -263412.54 0.61 0.22 0.14 0.03 0.14
## [7] 0.07 0.88 0.05 0.52 0.04
## [1] -263398.10 0.62 0.21 0.13 0.04 0.14
## [7] 0.07 0.88 0.05 0.52 0.04
## [1] -263384.48 0.62 0.21 0.13 0.04 0.14
## [7] 0.07 0.88 0.05 0.52 0.04
## [1] -263368.42 0.63 0.20 0.12 0.04 0.13
## [7] 0.06 0.88 0.05 0.52 0.04
## [1] -263350.22 0.63 0.20 0.12 0.05 0.13
## [7] 0.06 0.88 0.05 0.52 0.04
## [1] -263330.28 0.63 0.20 0.12 0.05 0.12
## [7] 0.06 0.88 0.05 0.52 0.04
## [1] -263309.02 0.63 0.19 0.12 0.05 0.12
## [7] 0.05 0.89 0.05 0.52 0.05
## [1] -263286.73 0.63 0.19 0.12 0.06 0.12
## [7] 0.05 0.89 0.05 0.51 0.05
## [1] -263264.21 0.64 0.19 0.12 0.06 0.12
## [7] 0.05 0.89 0.05 0.51 0.05
## [1] -263242.66 0.64 0.18 0.12 0.06 0.11
## [7] 0.05 0.89 0.05 0.51 0.05
## [1] -263222.78 0.64 0.18 0.12 0.06 0.11
## [7] 0.04 0.89 0.05 0.51 0.05
## [1] -263205.56 0.64 0.18 0.11 0.07 0.11
## [7] 0.04 0.89 0.05 0.51 0.06
## [1] -263191.81 0.64 0.18 0.11 0.07 0.11
## [7] 0.04 0.89 0.04 0.51 0.06
## [1] -263182.23 0.64 0.17 0.11 0.07 0.10
## [7] 0.04 0.89 0.04 0.50 0.06
## [1] 24
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -267783.99 0.55 0.24 0.19 0.02 0.14
## [7] 0.08 0.88 0.04 0.51 0.05
## [1] -264335.74 0.59 0.22 0.17 0.02 0.15
## [7] 0.08 0.86 0.04 0.52 0.05
## [1] -263835.02 0.61 0.20 0.16 0.03 0.16
## [7] 0.09 0.86 0.05 0.53 0.05
## [1] -263676.17 0.62 0.19 0.16 0.03 0.16
## [7] 0.09 0.85 0.05 0.53 0.04
## [1] -263627.80 0.62 0.19 0.15 0.03 0.16
## [7] 0.08 0.85 0.05 0.53 0.04
## [1] -263621.63 0.63 0.18 0.15 0.04 0.16
## [7] 0.08 0.84 0.05 0.54 0.04
## [1] 25
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -267731.20 0.56 0.23 0.19 0.02 0.15
## [7] 0.09 0.88 0.04 0.51 0.05
## [1] -264708.30 0.61 0.20 0.16 0.03 0.17
## [7] 0.10 0.87 0.04 0.51 0.04
## [1] -264313.02 0.63 0.19 0.15 0.03 0.17
## [7] 0.10 0.86 0.04 0.51 0.04
## [1] -264195.99 0.64 0.18 0.14 0.04 0.18
## [7] 0.11 0.86 0.04 0.52 0.04
## [1] -264157.86 0.64 0.18 0.14 0.04 0.18
## [7] 0.11 0.85 0.05 0.52 0.04
## [1] -264144.75 0.64 0.17 0.14 0.04 0.19
## [7] 0.11 0.85 0.05 0.52 0.04
## [1] -264137.49 0.65 0.17 0.14 0.05 0.19
## [7] 0.11 0.85 0.05 0.52 0.04
## [1] 26
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -269373.79 0.57 0.23 0.18 0.02 0.16
## [7] 0.09 0.87 0.03 0.51 0.05
## [1] -264818.67 0.61 0.21 0.15 0.02 0.18
## [7] 0.09 0.86 0.04 0.51 0.05
## [1] -264208.75 0.63 0.20 0.14 0.03 0.19
## [7] 0.09 0.85 0.04 0.52 0.05
## [1] -264018.42 0.64 0.19 0.14 0.03 0.19
## [7] 0.09 0.85 0.04 0.52 0.05
## [1] -263950.31 0.64 0.19 0.13 0.04 0.20
## [7] 0.10 0.84 0.04 0.52 0.05
## [1] -263926.62 0.64 0.19 0.13 0.04 0.20
## [7] 0.10 0.84 0.04 0.53 0.05
## [1] -263920.06 0.64 0.19 0.13 0.04 0.20
## [7] 0.10 0.84 0.04 0.53 0.05
## [1] 27
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -269824.44 0.58 0.22 0.18 0.02 0.16
## [7] 0.08 0.87 0.03 0.51 0.05
## [1] -264468.03 0.61 0.20 0.16 0.02 0.18
## [7] 0.08 0.86 0.03 0.51 0.05
## [1] -263797.43 0.63 0.19 0.15 0.03 0.19
## [7] 0.08 0.85 0.04 0.52 0.05
## [1] -263601.03 0.64 0.19 0.15 0.03 0.20
## [7] 0.08 0.85 0.04 0.53 0.05
## [1] -263538.19 0.64 0.18 0.14 0.04 0.20
## [7] 0.09 0.84 0.04 0.53 0.05
## [1] -263523.40 0.64 0.18 0.14 0.04 0.21
## [7] 0.09 0.84 0.04 0.54 0.05
## [1] -263527.43 0.63 0.18 0.14 0.04 0.21
## [7] 0.09 0.84 0.04 0.54 0.05
## [1] 28
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -266204.55 0.54 0.29 0.15 0.02 0.13
## [7] 0.08 0.88 0.03 0.51 0.05
## [1] -263710.54 0.58 0.27 0.12 0.03 0.14
## [7] 0.08 0.87 0.04 0.51 0.04
## [1] -263504.80 0.60 0.26 0.10 0.03 0.14
## [7] 0.08 0.86 0.04 0.52 0.04
## [1] -263452.41 0.61 0.25 0.09 0.04 0.13
## [7] 0.08 0.86 0.04 0.52 0.04
## [1] -263434.00 0.62 0.25 0.09 0.05 0.13
## [7] 0.08 0.86 0.04 0.52 0.04
## [1] -263424.67 0.62 0.24 0.09 0.05 0.13
## [7] 0.07 0.86 0.04 0.53 0.04
## [1] 29
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -267788.65 0.56 0.25 0.17 0.02 0.14
## [7] 0.09 0.88 0.04 0.51 0.05
## [1] -264511.04 0.60 0.23 0.14 0.02 0.15
## [7] 0.09 0.87 0.04 0.51 0.05
## [1] -264073.57 0.62 0.22 0.13 0.03 0.16
## [7] 0.09 0.86 0.04 0.52 0.05
## [1] -263913.12 0.63 0.21 0.13 0.03 0.16
## [7] 0.09 0.85 0.05 0.52 0.04
## [1] -263840.55 0.63 0.21 0.12 0.04 0.16
## [7] 0.09 0.85 0.05 0.53 0.04
## [1] -263804.20 0.63 0.20 0.12 0.04 0.16
## [7] 0.09 0.84 0.05 0.53 0.04
## [1] -263783.55 0.63 0.20 0.12 0.04 0.16
## [7] 0.09 0.84 0.05 0.53 0.04
## [1] -263769.56 0.63 0.20 0.12 0.05 0.16
## [7] 0.09 0.84 0.05 0.53 0.04
## [1] -263757.04 0.63 0.20 0.12 0.05 0.16
## [7] 0.09 0.84 0.05 0.54 0.05
## [1] -263743.71 0.63 0.20 0.12 0.05 0.15
## [7] 0.09 0.84 0.05 0.54 0.05
## [1] -263728.47 0.63 0.20 0.12 0.05 0.15
## [7] 0.08 0.84 0.05 0.54 0.05
## [1] -263710.86 0.62 0.20 0.12 0.06 0.15
## [7] 0.08 0.84 0.05 0.54 0.05
## [1] -263690.79 0.62 0.20 0.12 0.06 0.15
## [7] 0.08 0.84 0.05 0.54 0.05
## [1] -263668.41 0.62 0.20 0.13 0.06 0.15
## [7] 0.08 0.84 0.05 0.54 0.05
## [1] -263643.98 0.61 0.20 0.13 0.06 0.15
## [7] 0.08 0.84 0.05 0.54 0.05
## [1] -263617.89 0.61 0.20 0.13 0.06 0.15
## [7] 0.08 0.84 0.05 0.54 0.05
## [1] -263590.56 0.61 0.20 0.13 0.07 0.15
## [7] 0.08 0.84 0.05 0.53 0.05
## [1] -263562.23 0.61 0.20 0.13 0.07 0.15
## [7] 0.08 0.84 0.05 0.53 0.05
## [1] -263533.44 0.60 0.20 0.13 0.07 0.15
## [7] 0.08 0.84 0.05 0.53 0.05
## [1] -263504.42 0.60 0.20 0.13 0.07 0.15
## [7] 0.08 0.84 0.05 0.53 0.06
## [1] -263475.53 0.60 0.20 0.13 0.08 0.15
## [7] 0.08 0.84 0.05 0.53 0.06
## [1] -263447.02 0.59 0.20 0.13 0.08 0.14
## [7] 0.08 0.84 0.05 0.53 0.06
## [1] -263419.08 0.59 0.20 0.13 0.08 0.14
## [7] 0.08 0.84 0.05 0.53 0.06
## [1] -263391.89 0.59 0.20 0.13 0.08 0.14
## [7] 0.08 0.84 0.05 0.53 0.06
## [1] -263365.59 0.58 0.20 0.13 0.08 0.14
## [7] 0.07 0.84 0.05 0.53 0.06
## [1] -263340.26 0.58 0.20 0.13 0.09 0.14
## [7] 0.07 0.84 0.05 0.52 0.06
## [1] -263315.98 0.58 0.20 0.13 0.09 0.14
## [7] 0.07 0.84 0.05 0.52 0.06
## [1] -263292.80 0.57 0.20 0.13 0.09 0.14
## [7] 0.07 0.84 0.05 0.52 0.06
## [1] -263270.74 0.57 0.20 0.14 0.09 0.14
## [7] 0.07 0.84 0.05 0.52 0.07
## [1] -263249.81 0.57 0.20 0.14 0.10 0.14
## [7] 0.07 0.84 0.05 0.52 0.07
## [1] -263230.01 0.56 0.20 0.14 0.10 0.14
## [7] 0.07 0.84 0.05 0.52 0.07
## [1] -263211.31 0.56 0.20 0.14 0.10 0.14
## [7] 0.07 0.84 0.05 0.52 0.07
## [1] -263193.70 0.55 0.20 0.14 0.10 0.14
## [7] 0.07 0.84 0.05 0.52 0.07
## [1] -263177.14 0.55 0.20 0.14 0.11 0.14
## [7] 0.07 0.84 0.05 0.51 0.07
## [1] -263161.61 0.55 0.20 0.14 0.11 0.14
## [7] 0.07 0.84 0.05 0.51 0.07
## [1] -263147.06 0.54 0.20 0.14 0.11 0.14
## [7] 0.07 0.84 0.05 0.51 0.07
## [1] -263133.46 0.54 0.20 0.14 0.12 0.14
## [7] 0.07 0.84 0.05 0.51 0.07
## [1] -263120.76 0.54 0.20 0.14 0.12 0.14
## [7] 0.07 0.84 0.05 0.51 0.08
## [1] -263108.94 0.53 0.20 0.14 0.12 0.14
## [7] 0.07 0.84 0.05 0.51 0.08
## [1] -263097.94 0.53 0.20 0.14 0.12 0.14
## [7] 0.07 0.84 0.05 0.51 0.08
## [1] -263087.74 0.52 0.21 0.15 0.13 0.13
## [7] 0.07 0.84 0.05 0.51 0.08
## [1] -263078.30 0.52 0.21 0.15 0.13 0.13
## [7] 0.07 0.84 0.05 0.51 0.08
## [1] 30
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -265331.09 0.54 0.19 0.25 0.02 0.15
## [7] 0.09 0.89 0.04 0.51 0.05
## [1] -263250.28 0.59 0.16 0.23 0.02 0.16
## [7] 0.10 0.88 0.04 0.52 0.04
## [1] -262967.28 0.61 0.14 0.22 0.03 0.17
## [7] 0.10 0.88 0.04 0.53 0.04
## [1] -262859.40 0.62 0.13 0.22 0.04 0.17
## [7] 0.10 0.88 0.04 0.54 0.04
## [1] -262808.62 0.62 0.12 0.22 0.04 0.17
## [7] 0.10 0.88 0.04 0.54 0.04
## [1] -262779.47 0.62 0.11 0.22 0.04 0.17
## [7] 0.10 0.88 0.04 0.55 0.04
## [1] -262758.20 0.63 0.11 0.22 0.05 0.17
## [7] 0.10 0.88 0.04 0.55 0.04
## [1] -262739.49 0.62 0.11 0.22 0.05 0.17
## [7] 0.10 0.88 0.04 0.55 0.04
## [1] -262722.20 0.62 0.10 0.22 0.06 0.16
## [7] 0.10 0.88 0.04 0.56 0.04
## [1] -262705.72 0.62 0.10 0.22 0.06 0.16
## [7] 0.10 0.88 0.04 0.56 0.04
## [1] -262690.48 0.62 0.10 0.22 0.06 0.16
## [7] 0.09 0.88 0.04 0.56 0.04
## [1] -262676.98 0.62 0.10 0.22 0.07 0.16
## [7] 0.09 0.88 0.04 0.56 0.04
## [1] -262665.76 0.62 0.10 0.22 0.07 0.15
## [7] 0.09 0.88 0.04 0.56 0.04
## [1] -262657.20 0.61 0.10 0.22 0.07 0.15
## [7] 0.08 0.88 0.04 0.57 0.04
plts_paired_order<-plts_paired[order(sampleinfo_organoid_notfetal$passage.or.rescope.no_numeric)]
pdf(here("figs","MTAB4957_organoids_thresholding_all_samples.pdf"))
plts_paired_order
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dev.off()
## png
## 2
sampleinfo_organoid_fetal<-sampleinfo_organoid[which(sampleinfo_organoid$Characteristics.biosource.type.=="organoid" & sampleinfo_organoid$Characteristics.developmental.stage.=="fetal stage"),]
sampleinfo_organoid_fetal<-sampleinfo_organoid_fetal[-grep("KO", sampleinfo_organoid_fetal$condition),]
MTAB_organoid_beta_fetal<-MTAB_organoid_beta[,which(colnames(MTAB_organoid_beta)%in%sampleinfo_organoid_fetal$Assay.Name)]
identical(colnames(MTAB_organoid_beta_fetal),sampleinfo_organoid_fetal$Assay.Name)
## [1] TRUE
# ' ### PCA organoids
pca_res <- prcomp(t(MTAB_organoid_beta_fetal))
Loadings<-as.data.frame(pca_res$x)
vars <- pca_res$sdev^2
Importance<-vars/sum(vars)
meta_categorical <- sampleinfo_organoid_fetal[, c(4,8,13,17,18)] # input column numbers in meta that contain categorical variables
meta_continuous <- sampleinfo_organoid_fetal[, c(9,21)] # input column numbers in meta that contain continuous variables
colnames(meta_categorical) <- c("Individual", "Sample Site","Sex","Block","Sentrix ID")
colnames(meta_continuous) <- c("Age", "Passage")
meta_continuous$Age<-as.numeric(meta_continuous$Age)
meta_categorical$Block<-as.factor(meta_categorical$Block)
ord<-1:length(c(colnames(meta_categorical),colnames(meta_continuous)))
PCs_to_view<-10
suppressWarnings(heat_scree_plot(Loadings, Importance, 2.5, 2.7))
## PC vs PC plot
Loadings$Assay.Name<-rownames(Loadings)
Loadings_meta<-merge(Loadings, sampleinfo_organoid_fetal, by="Assay.Name")
Sample Site
ggplot(Loadings_meta, aes(PC1, PC2, fill=Characteristics.sampling.site.))+geom_point(shape=21,size=3, color="black")+theme_bw()+
xlab(paste("PC1 (",round(Importance[1]*100,0),"%)", sep=""))+ylab(paste("PC2 (",round(Importance[2]*100,0),"%)", sep=""))+th+theme(axis.text = element_text(size=12),
axis.title = element_text(size=14),
plot.margin = margin(1, 0.1, 1, 1, "cm"))
pc_plt<-ggplot(Loadings_meta, aes(PC1, PC2, fill=as.factor(passage.or.rescope.no_numeric)))+geom_line(aes(PC1,PC2, group=sample_ID), color="lightgrey")+#, color=sampling.time.point
geom_point(shape=21,size=3)+#
theme_bw()+xlab(paste("PC1 (",round(Importance[1]*100,0),"%)", sep=""))+ylab(paste("PC2 (",round(Importance[2]*100,0),"%)", sep=""))+th+theme(axis.text = element_text(size=12),axis.title = element_text(size=14))+
scale_fill_manual(values=c(colorRampPalette(brewer.pal(11, "Spectral"))(11), "#544791","#4a3e80", "#40366f","#221d3c"),name="Passage\nNumber")+scale_color_manual(values=c("black","white","black"))
legend<-ggplot(sampleinfo_organoid_fetal, aes(as.factor(-passage.or.rescope.no_numeric), fill=as.factor(passage.or.rescope.no_numeric)))+geom_bar(color="black")+
theme_bw()+theme(legend.position = "none", axis.text.y = element_blank(),
axis.title.y = element_blank(),
axis.ticks.y = element_blank(),
legend.title=element_text(size=10),
legend.text=element_text(size=8))+
coord_flip()+
scale_fill_manual(values=c(colorRampPalette(brewer.pal(11, "Spectral"))(11), "#544791","#4a3e80", "#40366f","#221d3c"),name="Passage\nNumber")+th
r <- ggplot() + theme_void()
grid.arrange(pc_plt,arrangeGrob(r,legend,r, heights=c(0.6,1.25,0.4)), ncol=2, widths=c(7,1))
Variation<-function(x) {quantile(x, c(0.9), na.rm=T)[[1]]-quantile(x, c(0.1), na.rm=T)[[1]]}
Mval<-function(beta) log2(beta/(1-beta))
MTAB4957_mval= apply(MTAB_organoid_beta_fetal, 1, Mval) # need mvalues for combat
MTAB4957_mval = as.data.frame(MTAB4957_mval)
MTAB4957_mval = t(MTAB4957_mval)
ref_range_dnam<-sapply(1:nrow(MTAB4957_mval), function(x) Variation(MTAB4957_mval[x,]))
dim(MTAB4957_beta_VeryVariable<-MTAB_organoid_beta_fetal[which(ref_range_dnam>=2.75),])# 28418
## [1] 28418 26
## Beta distribution plot
Beta_melted<- melt(MTAB4957_beta_VeryVariable)
Beta_Plot<-Beta_melted[which(!(is.na(Beta_melted$value))),]
colnames(Beta_Plot)<-c("CpG","ID","Beta")
Beta_Plot<-merge(Beta_Plot,sampleinfo_organoid_fetal, by.x="ID", by.y="Assay.Name")
Beta_Plot$passage.or.rescope.no_numeric.factor <- factor(Beta_Plot$passage.or.rescope.no_numeric, levels = c(23,21,14,12,9,7,6,5,3,2,1))
ggplot(Beta_Plot, aes(Beta,color=passage.or.rescope.no_numeric.factor))+
geom_density(size=1)+theme_bw()+xlab("DNAm Beta Value")+ylab("Density")+
scale_color_manual(values=pass_col, name="Passage\nNumber")+th+theme(legend.text = element_text(size=7),
legend.title = element_text(size=10),
legend.key.size = unit(0.7,"line"))
To view the beta distributions we will also include a line for the 11 primary fetal samples to compare each passage to primary
identical(colnames(organoid_fetal_primary),sampleinfo_fetal_primary$Assay.Name)
## [1] TRUE
MTAB4957_mval= apply(organoid_fetal_primary, 1, Mval) # need mvalues for combat
MTAB4957_mval = as.data.frame(MTAB4957_mval)
MTAB4957_mval = t(MTAB4957_mval)
ref_range_dnam_fetal<-sapply(1:nrow(MTAB4957_mval), function(x) Variation(MTAB4957_mval[x,]))
dim(organoid_fetal_primary_VeryVariable<-organoid_fetal_primary[rev(order(ref_range_dnam_fetal)),])
## [1] 409528 11
dim(organoid_fetal_primary_VeryVariable<-organoid_fetal_primary_VeryVariable[1:28418 ,])# same number as MTAB organoid varible
## [1] 28418 11
Beta_melted_MTAB_primary<- melt(organoid_fetal_primary_VeryVariable)
Beta_Plot_MTAB_primary<-Beta_melted_MTAB_primary[which(!(is.na(Beta_melted_MTAB_primary$value))),]
colnames(Beta_Plot_MTAB_primary)<-c("CpG","ID","Beta")
Beta_Plot_MTAB_primary<-merge(Beta_Plot_MTAB_primary,sampleinfo_fetal_primary, by.x="ID", by.y="Assay.Name")
Beta_plot_primary<-Beta_Plot_MTAB_primary[,c(1:3)]
Beta_plot_primary$passage.or.rescope.no_numeric<-0
Beta_Plot<-Beta_Plot[,c(1:3,23)]
Beta_Plot_combined<-rbind(Beta_plot_primary,Beta_Plot)
Beta_Plot_combined$passage.or.rescope.no_numeric.factor <- factor(Beta_Plot_combined$passage.or.rescope.no_numeric, levels = c(23,21,14,12,9,7,6,5,3,2,1,0))
ggplot(Beta_Plot_combined, aes(Beta,color=as.factor(passage.or.rescope.no_numeric.factor)))+
geom_density(size=1)+theme_bw()+xlab("DNAm Beta Value")+ylab("Density")+
scale_color_manual(values=pass_col, name="Passage\nNumber")+th+theme(legend.text = element_text(size=7),
legend.title = element_text(size=10),
legend.key.size = unit(0.7,"line"))
ggsave(here("figs","MTAB4957_beta_fetal_with_primary.pdf"),width = 3.75, height = 2.5)
ggsave(here("figs/jpeg","MTAB4957_beta_fetal_with_primary.jpeg"), w=5, h=3)
sampleinfo_organoid_fetal$sample_ID<-paste(sampleinfo_organoid_fetal$Characteristics.individual., sampleinfo_organoid_fetal$Characteristics.sampling.site.)
sampleinfo_organoid_paired<-sampleinfo_organoid_fetal[which(sampleinfo_organoid_fetal$sample_ID%in%sampleinfo_organoid_fetal$sample_ID[duplicated(sampleinfo_organoid_fetal$sample_ID)]),]
MTAB4957.organoid_paired<-do.call(rbind,lapply(1:length(unique(sampleinfo_organoid_paired$sample_ID)), function(x){
sample<-unique(sampleinfo_organoid_paired$sample_ID)[x]
samp<-sampleinfo_organoid_paired[sampleinfo_organoid_paired$sample_ID==sample,]
samp<-samp[order(samp$passage.or.rescope.no_numeric),]
samp$hilo<-as.factor(samp$passage.or.rescope.no_numeric)
if(length(levels(samp$hilo))==2){levels(samp$hilo)<-c("lower","higher")}else{
if(length(levels(samp$hilo))==3){levels(samp$hilo)<-c("lower","higher","highest")}else{
if(length(levels(samp$hilo))==4){levels(samp$hilo)<-c("lowest","lower","higher","highest")}else{samp$hilo<-NA}
}
}
samp
}))
MTAB4957.organoid_paired<-MTAB4957.organoid_paired[which(!is.na(MTAB4957.organoid_paired$hilo)),]
MTAB4957.organoid_paired$hilo<-factor(MTAB4957.organoid_paired$hilo, c("lowest","lower","higher","highest"))
identical(colnames(MTAB4957_beta_VeryVariable), sampleinfo_organoid_fetal$Assay.Name)
## [1] TRUE
MTAB4957_beta_VeryVariable_paird<-MTAB4957_beta_VeryVariable[,which(sampleinfo_organoid_fetal$sample_ID%in%MTAB4957.organoid_paired$sample_ID)]
Beta_melted<- melt(MTAB4957_beta_VeryVariable_paird)
Beta_Plot<-Beta_melted[which(!(is.na(Beta_melted$value))),]
colnames(Beta_Plot)<-c("CpG","ID","Beta")
Beta_Plot<-merge(Beta_Plot,MTAB4957.organoid_paired, by.x="ID", by.y="Assay.Name")
labels<-as.data.frame(tapply(MTAB4957.organoid_paired$passage.or.rescope.no_numeric, MTAB4957.organoid_paired$sample_ID, function(x) paste(x, collapse=", ")))
colnames(labels)<-"passge"
labels$sample_ID<-rownames(labels)
ggplot()+
geom_density(aes(Beta,color=hilo, group=ID),Beta_Plot, size=0.75)+theme_bw()+xlab("DNAm Beta Value")+ylab("Density")+
scale_color_manual(values = c ("#9ecae1","#4292c6", "#225ea8", "#081d58"), name="Relative\nPassage\nLevel within\nPatient")+facet_wrap(~sample_ID, nrow=2)+
geom_text(aes(0.5, 2.75, label=passge), data=labels, color="grey20")+th+theme(strip.text = element_text(size = 10),
axis.text=element_text(size=4),
panel.spacing = unit(0.7, "lines"))+
scale_x_continuous(breaks = c(0,0.5,1))
ggsave(here("figs","MTAB4957_beta_paired_fetal.pdf"),w=6, height = 3.75)
ggsave(here("figs/jpeg","MTAB4957_beta_paired_fetal.jpeg"), w=6, height = 3.75)
sampleinfo_organoid_fetal$thresholded_prior_ratio<-sapply(1:nrow(sampleinfo_organoid_fetal), function(x){
print(x)
converted<-as.numeric(round(MTAB4957_beta_VeryVariable[,x]*1000,0))
counts<-rep(1000, length(converted))
res = em(converted, counts, .41, .31, .27, 0.01, .1, .1, .90, .03, .5, .05)
passage_threshold_params(converted, counts, res)
})
## [1] 1
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -157952.80 0.56 0.28 0.14 0.02 0.14
## [7] 0.09 0.89 0.04 0.50 0.04
## [1] -156698.25 0.60 0.27 0.11 0.03 0.15
## [7] 0.09 0.88 0.04 0.50 0.04
## [1] -156685.93 0.62 0.26 0.09 0.04 0.15
## [7] 0.09 0.88 0.05 0.50 0.03
## [1] -156733.66 0.63 0.25 0.08 0.05 0.15
## [7] 0.09 0.88 0.05 0.50 0.03
## [1] -156784.92 0.63 0.24 0.07 0.05 0.15
## [7] 0.09 0.88 0.05 0.50 0.03
## [1] -156828.44 0.63 0.24 0.07 0.06 0.15
## [7] 0.09 0.88 0.05 0.50 0.03
## [1] -156863.15 0.63 0.24 0.06 0.07 0.15
## [7] 0.09 0.88 0.04 0.50 0.03
## [1] -156890.89 0.63 0.23 0.06 0.07 0.14
## [7] 0.08 0.88 0.04 0.50 0.03
## [1] -156912.20 0.63 0.23 0.06 0.08 0.14
## [7] 0.08 0.88 0.04 0.50 0.03
## [1] -156929.66 0.63 0.23 0.06 0.08 0.14
## [7] 0.08 0.89 0.04 0.50 0.03
## [1] -156944.50 0.63 0.23 0.06 0.09 0.14
## [7] 0.08 0.89 0.04 0.50 0.03
## [1] -156957.82 0.62 0.23 0.06 0.09 0.13
## [7] 0.07 0.89 0.04 0.50 0.03
## [1] -156970.26 0.62 0.22 0.06 0.09 0.13
## [7] 0.07 0.89 0.03 0.50 0.04
## [1] -156982.27 0.62 0.22 0.06 0.10 0.13
## [7] 0.07 0.89 0.03 0.50 0.04
## [1] -156994.24 0.62 0.22 0.06 0.10 0.13
## [7] 0.07 0.89 0.03 0.50 0.04
## [1] -157006.40 0.62 0.22 0.06 0.11 0.12
## [7] 0.07 0.90 0.03 0.49 0.04
## [1] -157018.95 0.62 0.22 0.06 0.11 0.12
## [7] 0.06 0.90 0.03 0.49 0.04
## [1] -157032.07 0.62 0.22 0.06 0.11 0.12
## [7] 0.06 0.90 0.03 0.49 0.04
## [1] -157046.11 0.61 0.21 0.06 0.12 0.12
## [7] 0.06 0.90 0.03 0.49 0.05
## [1] -157060.79 0.61 0.21 0.06 0.12 0.12
## [7] 0.06 0.90 0.03 0.49 0.05
## [1] -157076.20 0.61 0.21 0.06 0.12 0.11
## [7] 0.06 0.90 0.03 0.49 0.05
## [1] -157092.33 0.61 0.21 0.06 0.13 0.11
## [7] 0.05 0.90 0.02 0.48 0.05
## [1] -157109.19 0.61 0.21 0.06 0.13 0.11
## [7] 0.05 0.91 0.02 0.48 0.05
## [1] -157127.55 0.61 0.21 0.06 0.13 0.11
## [7] 0.05 0.91 0.02 0.48 0.06
## [1] -157146.52 0.61 0.20 0.06 0.13 0.11
## [7] 0.05 0.91 0.02 0.48 0.06
## [1] -157166.10 0.61 0.20 0.05 0.14 0.11
## [7] 0.05 0.91 0.02 0.48 0.06
## [1] -157186.25 0.60 0.20 0.05 0.14 0.10
## [7] 0.05 0.91 0.02 0.47 0.06
## [1] -157206.95 0.60 0.20 0.05 0.14 0.10
## [7] 0.04 0.91 0.02 0.47 0.06
## [1] -157228.14 0.60 0.20 0.05 0.15 0.10
## [7] 0.04 0.91 0.02 0.47 0.07
## [1] -157249.76 0.60 0.19 0.05 0.15 0.10
## [7] 0.04 0.91 0.02 0.47 0.07
## [1] -157271.76 0.60 0.19 0.05 0.15 0.10
## [7] 0.04 0.91 0.02 0.47 0.07
## [1] -157294.09 0.60 0.19 0.05 0.16 0.10
## [7] 0.04 0.91 0.02 0.46 0.07
## [1] -157316.67 0.60 0.19 0.05 0.16 0.09
## [7] 0.04 0.91 0.02 0.46 0.08
## [1] -157339.47 0.60 0.19 0.05 0.16 0.09
## [7] 0.04 0.91 0.02 0.46 0.08
## [1] -157362.41 0.59 0.19 0.05 0.17 0.09
## [7] 0.03 0.91 0.02 0.46 0.08
## [1] -157383.97 0.59 0.18 0.05 0.17 0.09
## [7] 0.03 0.91 0.02 0.46 0.08
## [1] -157405.81 0.59 0.18 0.05 0.17 0.09
## [7] 0.03 0.91 0.02 0.46 0.08
## [1] -157427.80 0.59 0.18 0.05 0.17 0.09
## [7] 0.03 0.91 0.02 0.45 0.09
## [1] -157449.85 0.59 0.18 0.05 0.18 0.09
## [7] 0.03 0.92 0.02 0.45 0.09
## [1] -157471.88 0.59 0.18 0.05 0.18 0.09
## [7] 0.03 0.92 0.02 0.45 0.09
## [1] -157493.85 0.59 0.18 0.05 0.18 0.09
## [7] 0.03 0.92 0.02 0.45 0.09
## [1] -157515.72 0.58 0.18 0.05 0.19 0.08
## [7] 0.03 0.92 0.02 0.45 0.10
## [1] -157537.45 0.58 0.18 0.05 0.19 0.08
## [7] 0.03 0.92 0.02 0.45 0.10
## [1] -157559.01 0.58 0.17 0.05 0.19 0.08
## [7] 0.03 0.92 0.02 0.45 0.10
## [1] -157580.39 0.58 0.17 0.05 0.19 0.08
## [7] 0.03 0.92 0.02 0.44 0.10
## [1] -157601.56 0.58 0.17 0.05 0.20 0.08
## [7] 0.03 0.92 0.02 0.44 0.10
## [1] -157622.51 0.58 0.17 0.05 0.20 0.08
## [7] 0.03 0.92 0.02 0.44 0.11
## [1] -157643.23 0.57 0.17 0.05 0.20 0.08
## [7] 0.03 0.92 0.02 0.44 0.11
## [1] -157663.67 0.57 0.17 0.05 0.21 0.08
## [7] 0.02 0.92 0.02 0.44 0.11
## [1] -157683.93 0.57 0.17 0.05 0.21 0.08
## [7] 0.02 0.92 0.02 0.44 0.11
## [1] -157703.91 0.57 0.17 0.05 0.21 0.08
## [7] 0.02 0.92 0.02 0.44 0.12
## [1] -157723.64 0.57 0.17 0.05 0.22 0.08
## [7] 0.02 0.92 0.02 0.44 0.12
## [1] -157743.11 0.56 0.16 0.05 0.22 0.08
## [7] 0.02 0.92 0.02 0.44 0.12
## [1] -157762.32 0.56 0.16 0.05 0.22 0.08
## [7] 0.02 0.92 0.02 0.43 0.12
## [1] -157781.27 0.56 0.16 0.05 0.22 0.08
## [7] 0.02 0.92 0.02 0.43 0.12
## [1] -157799.96 0.56 0.16 0.06 0.23 0.08
## [7] 0.02 0.92 0.02 0.43 0.13
## [1] -157818.40 0.55 0.16 0.06 0.23 0.07
## [7] 0.02 0.92 0.02 0.43 0.13
## [1] -157834.71 0.55 0.16 0.06 0.23 0.07
## [7] 0.02 0.92 0.02 0.43 0.13
## [1] -157851.11 0.55 0.16 0.06 0.24 0.07
## [7] 0.02 0.92 0.02 0.43 0.13
## [1] -157867.58 0.55 0.16 0.06 0.24 0.07
## [7] 0.02 0.92 0.02 0.43 0.13
## [1] -157884.01 0.54 0.16 0.06 0.24 0.07
## [7] 0.02 0.92 0.02 0.43 0.14
## [1] -157901.25 0.54 0.16 0.06 0.25 0.07
## [7] 0.02 0.92 0.02 0.43 0.14
## [1] -157917.48 0.54 0.16 0.06 0.25 0.07
## [7] 0.02 0.92 0.02 0.43 0.14
## [1] -157934.18 0.53 0.16 0.06 0.25 0.07
## [7] 0.02 0.92 0.02 0.43 0.14
## [1] -157950.71 0.53 0.16 0.06 0.26 0.07
## [7] 0.02 0.92 0.02 0.43 0.14
## [1] -157966.87 0.53 0.15 0.06 0.26 0.07
## [7] 0.02 0.92 0.02 0.43 0.15
## [1] -157982.65 0.53 0.15 0.06 0.26 0.07
## [7] 0.02 0.92 0.02 0.43 0.15
## [1] -157998.21 0.52 0.15 0.06 0.27 0.07
## [7] 0.02 0.92 0.02 0.43 0.15
## [1] -158013.41 0.52 0.15 0.06 0.27 0.07
## [7] 0.02 0.92 0.02 0.43 0.15
## [1] -158028.30 0.52 0.15 0.06 0.27 0.07
## [7] 0.02 0.92 0.02 0.43 0.15
## [1] -158042.86 0.51 0.15 0.06 0.28 0.07
## [7] 0.02 0.92 0.02 0.43 0.15
## [1] -158057.09 0.51 0.15 0.06 0.28 0.07
## [7] 0.02 0.92 0.02 0.43 0.16
## [1] -158070.99 0.51 0.15 0.06 0.28 0.07
## [7] 0.02 0.92 0.02 0.43 0.16
## [1] -158084.55 0.50 0.15 0.06 0.29 0.07
## [7] 0.02 0.92 0.02 0.43 0.16
## [1] -158097.78 0.50 0.15 0.06 0.29 0.07
## [7] 0.02 0.92 0.02 0.43 0.16
## [1] -158110.65 0.50 0.15 0.06 0.29 0.07
## [7] 0.02 0.92 0.02 0.43 0.16
## [1] -158123.16 0.49 0.15 0.06 0.30 0.07
## [7] 0.02 0.92 0.02 0.43 0.16
## [1] -158135.34 0.49 0.15 0.06 0.30 0.07
## [7] 0.02 0.92 0.02 0.43 0.16
## [1] -158147.16 0.49 0.15 0.06 0.30 0.07
## [7] 0.02 0.92 0.02 0.43 0.17
## [1] -158158.39 0.48 0.15 0.06 0.31 0.07
## [7] 0.02 0.92 0.02 0.43 0.17
## [1] -158169.94 0.48 0.15 0.06 0.31 0.07
## [7] 0.02 0.92 0.02 0.43 0.17
## [1] -158180.40 0.48 0.15 0.06 0.32 0.07
## [7] 0.02 0.92 0.02 0.43 0.17
## [1] -158191.34 0.47 0.15 0.06 0.32 0.07
## [7] 0.02 0.92 0.02 0.43 0.17
## [1] -158200.68 0.47 0.15 0.06 0.32 0.07
## [7] 0.02 0.92 0.02 0.43 0.17
## [1] 2
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -159957.90 0.58 0.16 0.24 0.02 0.17
## [7] 0.10 0.87 0.03 0.52 0.05
## [1] -156264.73 0.62 0.12 0.24 0.03 0.19
## [7] 0.11 0.85 0.03 0.54 0.05
## [1] -155514.48 0.62 0.10 0.25 0.03 0.21
## [7] 0.11 0.84 0.03 0.55 0.04
## [1] -155286.99 0.62 0.09 0.25 0.04 0.23
## [7] 0.12 0.83 0.03 0.56 0.04
## [1] -155230.55 0.62 0.08 0.26 0.04 0.24
## [7] 0.12 0.83 0.03 0.56 0.04
## [1] -155236.15 0.61 0.08 0.26 0.05 0.25
## [7] 0.13 0.83 0.04 0.57 0.04
## [1] 3
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -156851.65 0.52 0.33 0.14 0.02 0.13
## [7] 0.08 0.90 0.04 0.49 0.04
## [1] -155670.41 0.54 0.33 0.11 0.02 0.13
## [7] 0.08 0.90 0.04 0.49 0.04
## [1] -155746.33 0.56 0.32 0.09 0.03 0.13
## [7] 0.08 0.90 0.04 0.49 0.04
## [1] -155871.81 0.56 0.32 0.08 0.03 0.13
## [7] 0.08 0.91 0.04 0.48 0.03
## [1] -155999.20 0.57 0.31 0.08 0.04 0.13
## [7] 0.08 0.91 0.04 0.48 0.03
## [1] -156117.45 0.57 0.31 0.08 0.05 0.13
## [7] 0.07 0.91 0.03 0.48 0.03
## [1] -156221.30 0.57 0.31 0.07 0.05 0.13
## [7] 0.07 0.92 0.03 0.47 0.03
## [1] -156307.54 0.57 0.30 0.07 0.06 0.13
## [7] 0.07 0.92 0.03 0.47 0.03
## [1] -156375.50 0.57 0.30 0.07 0.06 0.12
## [7] 0.07 0.92 0.03 0.47 0.03
## [1] -156424.53 0.57 0.30 0.07 0.06 0.12
## [7] 0.07 0.92 0.02 0.47 0.03
## [1] -156456.09 0.57 0.30 0.07 0.07 0.12
## [7] 0.06 0.93 0.02 0.46 0.03
## [1] -156472.42 0.56 0.30 0.07 0.07 0.12
## [7] 0.06 0.93 0.02 0.46 0.03
## [1] -156474.93 0.56 0.29 0.07 0.08 0.12
## [7] 0.06 0.93 0.02 0.46 0.03
## [1] 4
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -155944.91 0.46 0.43 0.10 0.01 0.12
## [7] 0.06 0.89 0.04 0.48 0.05
## [1] -153982.54 0.45 0.47 0.07 0.01 0.12
## [7] 0.06 0.90 0.04 0.47 0.04
## [1] -153857.92 0.44 0.48 0.06 0.02 0.12
## [7] 0.06 0.90 0.04 0.46 0.04
## [1] -153888.03 0.44 0.49 0.05 0.02 0.12
## [7] 0.06 0.90 0.04 0.45 0.04
## [1] -153959.91 0.44 0.49 0.05 0.02 0.12
## [7] 0.06 0.91 0.03 0.45 0.04
## [1] -154040.24 0.44 0.49 0.04 0.03 0.12
## [7] 0.06 0.91 0.03 0.44 0.03
## [1] -154113.45 0.44 0.48 0.04 0.03 0.12
## [7] 0.06 0.91 0.03 0.43 0.03
## [1] -154171.74 0.44 0.48 0.04 0.03 0.12
## [7] 0.06 0.91 0.03 0.43 0.03
## [1] -154211.24 0.44 0.48 0.04 0.04 0.11
## [7] 0.06 0.92 0.02 0.42 0.03
## [1] -154230.92 0.44 0.48 0.04 0.04 0.11
## [7] 0.05 0.92 0.02 0.42 0.03
## [1] -154231.47 0.43 0.48 0.04 0.05 0.11
## [7] 0.05 0.92 0.02 0.42 0.03
## [1] 5
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -156833.58 0.51 0.39 0.09 0.02 0.12
## [7] 0.07 0.88 0.04 0.49 0.04
## [1] -155288.23 0.51 0.41 0.05 0.02 0.12
## [7] 0.07 0.88 0.04 0.48 0.04
## [1] -155206.60 0.52 0.42 0.04 0.03 0.12
## [7] 0.07 0.88 0.04 0.47 0.03
## [1] -155226.02 0.52 0.42 0.03 0.04 0.12
## [7] 0.07 0.88 0.04 0.46 0.03
## [1] -155267.09 0.52 0.41 0.02 0.04 0.12
## [7] 0.07 0.88 0.04 0.46 0.03
## [1] -155306.10 0.51 0.41 0.02 0.05 0.12
## [7] 0.07 0.88 0.04 0.45 0.03
## [1] -155334.58 0.51 0.41 0.02 0.06 0.12
## [7] 0.07 0.88 0.04 0.45 0.03
## [1] -155350.38 0.50 0.41 0.02 0.07 0.12
## [7] 0.06 0.88 0.04 0.45 0.03
## [1] -155354.20 0.50 0.41 0.02 0.08 0.12
## [7] 0.06 0.89 0.03 0.44 0.03
## [1] 6
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -157509.21 0.54 0.25 0.19 0.02 0.13
## [7] 0.09 0.88 0.04 0.51 0.04
## [1] -156289.32 0.59 0.22 0.17 0.03 0.13
## [7] 0.09 0.87 0.04 0.52 0.04
## [1] -156129.04 0.61 0.20 0.15 0.03 0.13
## [7] 0.08 0.87 0.05 0.53 0.04
## [1] -156091.06 0.62 0.19 0.15 0.04 0.13
## [7] 0.08 0.86 0.05 0.53 0.03
## [1] -156095.91 0.62 0.19 0.15 0.04 0.12
## [7] 0.08 0.86 0.05 0.53 0.03
## [1] 7
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -158735.16 0.57 0.29 0.11 0.02 0.13
## [7] 0.09 0.87 0.04 0.50 0.04
## [1] -157153.62 0.62 0.28 0.08 0.03 0.14
## [7] 0.09 0.86 0.05 0.51 0.04
## [1] -156846.37 0.63 0.27 0.06 0.04 0.15
## [7] 0.09 0.84 0.06 0.51 0.04
## [1] -156673.36 0.64 0.26 0.05 0.05 0.15
## [7] 0.10 0.83 0.06 0.51 0.04
## [1] -156555.97 0.64 0.25 0.05 0.06 0.15
## [7] 0.09 0.81 0.07 0.51 0.04
## [1] -156470.97 0.64 0.25 0.04 0.06 0.14
## [7] 0.09 0.80 0.07 0.51 0.03
## [1] -156406.80 0.64 0.25 0.04 0.07 0.14
## [7] 0.09 0.79 0.07 0.51 0.04
## [1] -156355.33 0.64 0.25 0.04 0.08 0.14
## [7] 0.09 0.78 0.07 0.51 0.04
## [1] -156311.68 0.63 0.25 0.04 0.08 0.14
## [7] 0.09 0.78 0.07 0.51 0.04
## [1] -156272.32 0.63 0.24 0.04 0.09 0.14
## [7] 0.08 0.77 0.08 0.51 0.04
## [1] -156234.85 0.63 0.24 0.04 0.09 0.13
## [7] 0.08 0.76 0.08 0.51 0.04
## [1] -156197.68 0.62 0.24 0.04 0.10 0.13
## [7] 0.08 0.76 0.08 0.50 0.04
## [1] -156159.84 0.62 0.24 0.04 0.10 0.13
## [7] 0.08 0.76 0.08 0.50 0.04
## [1] -156120.89 0.62 0.24 0.04 0.10 0.13
## [7] 0.07 0.75 0.08 0.50 0.04
## [1] -156080.77 0.61 0.24 0.04 0.11 0.12
## [7] 0.07 0.75 0.08 0.50 0.04
## [1] -156039.62 0.61 0.24 0.04 0.11 0.12
## [7] 0.07 0.75 0.08 0.50 0.05
## [1] -155997.75 0.61 0.23 0.04 0.12 0.12
## [7] 0.07 0.74 0.08 0.49 0.05
## [1] -155955.50 0.61 0.23 0.04 0.12 0.12
## [7] 0.07 0.74 0.08 0.49 0.05
## [1] -155913.25 0.60 0.23 0.04 0.12 0.11
## [7] 0.06 0.74 0.08 0.49 0.05
## [1] -155871.36 0.60 0.23 0.04 0.13 0.11
## [7] 0.06 0.74 0.08 0.48 0.05
## [1] -155830.18 0.60 0.23 0.04 0.13 0.11
## [7] 0.06 0.74 0.08 0.48 0.06
## [1] -155790.02 0.60 0.22 0.05 0.13 0.11
## [7] 0.06 0.74 0.08 0.48 0.06
## [1] -155751.15 0.60 0.22 0.05 0.14 0.11
## [7] 0.05 0.74 0.08 0.47 0.06
## [1] -155713.78 0.59 0.22 0.05 0.14 0.10
## [7] 0.05 0.74 0.08 0.47 0.06
## [1] -155678.12 0.59 0.22 0.05 0.14 0.10
## [7] 0.05 0.73 0.08 0.47 0.06
## [1] -155644.30 0.59 0.22 0.05 0.15 0.10
## [7] 0.05 0.73 0.08 0.47 0.06
## [1] -155612.46 0.59 0.21 0.05 0.15 0.10
## [7] 0.05 0.73 0.08 0.46 0.07
## [1] -155582.68 0.58 0.21 0.05 0.15 0.10
## [7] 0.05 0.73 0.08 0.46 0.07
## [1] -155555.02 0.58 0.21 0.05 0.16 0.09
## [7] 0.04 0.73 0.08 0.46 0.07
## [1] -155529.53 0.58 0.21 0.05 0.16 0.09
## [7] 0.04 0.73 0.08 0.45 0.07
## [1] -155506.18 0.58 0.21 0.05 0.16 0.09
## [7] 0.04 0.73 0.08 0.45 0.07
## [1] -155484.98 0.58 0.20 0.05 0.17 0.09
## [7] 0.04 0.73 0.08 0.45 0.08
## [1] -155465.90 0.57 0.20 0.05 0.17 0.09
## [7] 0.04 0.73 0.08 0.44 0.08
## [1] -155448.90 0.57 0.20 0.05 0.17 0.09
## [7] 0.04 0.73 0.08 0.44 0.08
## [1] -155433.91 0.57 0.20 0.05 0.18 0.08
## [7] 0.03 0.73 0.08 0.44 0.08
## [1] -155420.85 0.57 0.20 0.05 0.18 0.08
## [7] 0.03 0.73 0.08 0.44 0.08
## [1] -155409.65 0.57 0.19 0.05 0.18 0.08
## [7] 0.03 0.73 0.08 0.43 0.09
## [1] -155400.20 0.57 0.19 0.06 0.19 0.08
## [7] 0.03 0.73 0.08 0.43 0.09
## [1] 8
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -160911.83 0.60 0.22 0.16 0.02 0.15
## [7] 0.09 0.86 0.03 0.51 0.05
## [1] -157017.47 0.64 0.19 0.14 0.03 0.17
## [7] 0.09 0.83 0.03 0.53 0.05
## [1] -156265.90 0.66 0.17 0.14 0.03 0.18
## [7] 0.10 0.82 0.03 0.54 0.04
## [1] -156048.24 0.66 0.16 0.14 0.04 0.18
## [7] 0.10 0.81 0.03 0.54 0.04
## [1] -156013.35 0.66 0.16 0.14 0.05 0.18
## [7] 0.10 0.80 0.03 0.55 0.04
## [1] -156040.19 0.65 0.15 0.14 0.05 0.19
## [7] 0.10 0.79 0.03 0.55 0.04
## [1] -156080.95 0.64 0.15 0.15 0.06 0.19
## [7] 0.10 0.79 0.03 0.55 0.04
## [1] -156117.44 0.63 0.15 0.15 0.06 0.19
## [7] 0.10 0.79 0.04 0.55 0.04
## [1] -156143.41 0.63 0.15 0.15 0.07 0.19
## [7] 0.10 0.79 0.04 0.55 0.04
## [1] -156158.45 0.62 0.16 0.16 0.07 0.19
## [7] 0.10 0.79 0.04 0.55 0.04
## [1] -156163.92 0.61 0.16 0.16 0.07 0.19
## [7] 0.10 0.78 0.04 0.55 0.04
## [1] 9
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -161638.23 0.62 0.19 0.16 0.02 0.17
## [7] 0.09 0.85 0.03 0.51 0.05
## [1] -157142.69 0.67 0.16 0.14 0.03 0.20
## [7] 0.10 0.83 0.03 0.53 0.04
## [1] -156228.96 0.68 0.14 0.14 0.04 0.21
## [7] 0.10 0.82 0.03 0.54 0.04
## [1] -155950.29 0.68 0.13 0.14 0.05 0.22
## [7] 0.10 0.81 0.03 0.54 0.04
## [1] -155898.64 0.67 0.13 0.15 0.05 0.23
## [7] 0.11 0.80 0.03 0.55 0.04
## [1] -155929.48 0.66 0.13 0.15 0.06 0.24
## [7] 0.11 0.79 0.03 0.55 0.04
## [1] -155982.66 0.65 0.13 0.15 0.07 0.25
## [7] 0.11 0.79 0.03 0.55 0.04
## [1] -156033.41 0.64 0.13 0.16 0.07 0.25
## [7] 0.11 0.79 0.04 0.55 0.04
## [1] -156072.50 0.63 0.13 0.16 0.08 0.25
## [7] 0.11 0.78 0.04 0.56 0.04
## [1] -156098.63 0.62 0.14 0.16 0.08 0.25
## [7] 0.11 0.78 0.04 0.56 0.04
## [1] -156113.57 0.61 0.14 0.17 0.08 0.25
## [7] 0.11 0.78 0.04 0.56 0.04
## [1] -156119.65 0.60 0.14 0.17 0.09 0.26
## [7] 0.11 0.78 0.04 0.56 0.04
## [1] 10
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -159328.07 0.58 0.22 0.18 0.02 0.15
## [7] 0.09 0.88 0.04 0.51 0.05
## [1] -157205.70 0.63 0.19 0.16 0.03 0.16
## [7] 0.09 0.86 0.05 0.52 0.04
## [1] -156780.59 0.65 0.17 0.15 0.03 0.17
## [7] 0.10 0.85 0.05 0.53 0.04
## [1] -156623.68 0.66 0.15 0.15 0.04 0.17
## [7] 0.10 0.84 0.06 0.54 0.04
## [1] -156571.96 0.66 0.15 0.15 0.04 0.17
## [7] 0.10 0.83 0.06 0.54 0.04
## [1] -156564.38 0.66 0.14 0.15 0.05 0.17
## [7] 0.10 0.83 0.06 0.55 0.04
## [1] 11
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -159121.75 0.57 0.27 0.13 0.02 0.14
## [7] 0.08 0.88 0.04 0.51 0.04
## [1] -157128.16 0.62 0.25 0.10 0.03 0.15
## [7] 0.08 0.86 0.05 0.52 0.04
## [1] -156774.55 0.64 0.24 0.09 0.04 0.15
## [7] 0.08 0.84 0.06 0.52 0.04
## [1] -156614.88 0.65 0.23 0.08 0.04 0.15
## [7] 0.08 0.83 0.06 0.53 0.04
## [1] -156536.74 0.65 0.22 0.08 0.05 0.14
## [7] 0.08 0.82 0.07 0.53 0.04
## [1] -156500.39 0.65 0.22 0.07 0.06 0.14
## [7] 0.08 0.81 0.07 0.53 0.04
## [1] -156485.06 0.65 0.21 0.07 0.06 0.14
## [7] 0.07 0.80 0.07 0.53 0.04
## [1] -156478.36 0.65 0.21 0.07 0.07 0.14
## [7] 0.07 0.80 0.07 0.53 0.04
## [1] 12
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -158970.73 0.57 0.17 0.24 0.02 0.16
## [7] 0.09 0.87 0.03 0.52 0.05
## [1] -155942.14 0.60 0.14 0.24 0.02 0.18
## [7] 0.10 0.86 0.03 0.53 0.05
## [1] -155480.73 0.61 0.12 0.24 0.03 0.19
## [7] 0.10 0.85 0.03 0.54 0.04
## [1] -155333.87 0.62 0.11 0.24 0.04 0.20
## [7] 0.10 0.85 0.03 0.55 0.04
## [1] -155281.81 0.62 0.10 0.24 0.04 0.21
## [7] 0.11 0.85 0.03 0.56 0.04
## [1] -155266.11 0.61 0.10 0.24 0.05 0.21
## [7] 0.11 0.84 0.03 0.56 0.04
## [1] -155264.73 0.61 0.10 0.24 0.05 0.21
## [7] 0.11 0.84 0.03 0.56 0.04
## [1] 13
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -160493.51 0.60 0.20 0.18 0.02 0.16
## [7] 0.09 0.86 0.03 0.52 0.05
## [1] -156901.58 0.64 0.16 0.17 0.03 0.18
## [7] 0.10 0.84 0.03 0.53 0.04
## [1] -156246.35 0.66 0.14 0.16 0.04 0.19
## [7] 0.10 0.83 0.03 0.54 0.04
## [1] -156042.13 0.66 0.13 0.16 0.04 0.20
## [7] 0.11 0.82 0.03 0.54 0.04
## [1] -155991.69 0.66 0.13 0.16 0.05 0.21
## [7] 0.11 0.82 0.04 0.55 0.04
## [1] -155998.34 0.65 0.12 0.17 0.06 0.21
## [7] 0.11 0.81 0.04 0.55 0.04
## [1] 14
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -157985.66 0.55 0.15 0.29 0.02 0.17
## [7] 0.09 0.88 0.03 0.52 0.05
## [1] -155298.48 0.57 0.11 0.29 0.02 0.19
## [7] 0.10 0.87 0.03 0.53 0.05
## [1] -154875.77 0.58 0.09 0.30 0.03 0.21
## [7] 0.10 0.86 0.03 0.54 0.04
## [1] -154731.59 0.58 0.08 0.30 0.03 0.22
## [7] 0.11 0.86 0.03 0.55 0.04
## [1] -154675.01 0.58 0.08 0.30 0.04 0.23
## [7] 0.11 0.86 0.03 0.55 0.04
## [1] -154653.48 0.58 0.07 0.30 0.04 0.24
## [7] 0.11 0.85 0.03 0.56 0.04
## [1] -154646.39 0.58 0.07 0.31 0.05 0.24
## [7] 0.12 0.85 0.04 0.56 0.04
## [1] 15
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -160561.43 0.60 0.20 0.18 0.02 0.16
## [7] 0.09 0.86 0.03 0.51 0.05
## [1] -156955.27 0.64 0.17 0.17 0.03 0.18
## [7] 0.09 0.84 0.03 0.52 0.05
## [1] -156310.09 0.65 0.15 0.16 0.03 0.20
## [7] 0.10 0.83 0.04 0.53 0.04
## [1] -156116.99 0.66 0.14 0.16 0.04 0.21
## [7] 0.10 0.82 0.04 0.54 0.04
## [1] -156074.73 0.66 0.13 0.17 0.04 0.21
## [7] 0.11 0.82 0.04 0.54 0.04
## [1] -156085.66 0.65 0.13 0.17 0.05 0.22
## [7] 0.11 0.81 0.04 0.55 0.04
## [1] -156111.46 0.65 0.13 0.17 0.05 0.22
## [7] 0.11 0.81 0.04 0.55 0.04
## [1] -156137.18 0.64 0.13 0.17 0.06 0.22
## [7] 0.11 0.81 0.04 0.55 0.04
## [1] -156157.47 0.63 0.13 0.17 0.06 0.22
## [7] 0.11 0.81 0.04 0.55 0.04
## [1] -156171.15 0.63 0.13 0.18 0.06 0.22
## [7] 0.11 0.81 0.04 0.55 0.04
## [1] -156179.01 0.62 0.13 0.18 0.07 0.23
## [7] 0.11 0.81 0.04 0.55 0.04
## [1] 16
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -158513.30 0.55 0.18 0.25 0.02 0.16
## [7] 0.09 0.87 0.03 0.52 0.05
## [1] -155719.03 0.59 0.15 0.24 0.02 0.17
## [7] 0.10 0.86 0.03 0.53 0.05
## [1] -155339.86 0.60 0.13 0.24 0.03 0.18
## [7] 0.10 0.86 0.03 0.54 0.05
## [1] -155213.01 0.61 0.12 0.24 0.03 0.19
## [7] 0.10 0.85 0.03 0.55 0.04
## [1] -155159.48 0.61 0.11 0.24 0.04 0.19
## [7] 0.10 0.85 0.03 0.55 0.04
## [1] -155135.64 0.60 0.11 0.24 0.04 0.20
## [7] 0.11 0.85 0.03 0.56 0.04
## [1] -155125.08 0.60 0.11 0.25 0.05 0.20
## [7] 0.11 0.85 0.03 0.56 0.04
## [1] -155120.02 0.60 0.11 0.25 0.05 0.20
## [7] 0.11 0.85 0.03 0.57 0.04
## [1] 17
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -158305.37 0.55 0.16 0.27 0.02 0.16
## [7] 0.09 0.87 0.03 0.52 0.05
## [1] -155471.42 0.58 0.12 0.27 0.02 0.18
## [7] 0.10 0.86 0.03 0.53 0.05
## [1] -155064.01 0.60 0.11 0.27 0.03 0.20
## [7] 0.11 0.86 0.03 0.54 0.04
## [1] -154924.29 0.60 0.10 0.27 0.03 0.21
## [7] 0.11 0.85 0.03 0.54 0.04
## [1] -154863.56 0.60 0.09 0.27 0.04 0.22
## [7] 0.12 0.85 0.03 0.55 0.04
## [1] -154834.50 0.60 0.09 0.27 0.04 0.22
## [7] 0.12 0.85 0.03 0.55 0.04
## [1] -154819.06 0.59 0.08 0.28 0.05 0.23
## [7] 0.12 0.85 0.03 0.56 0.04
## [1] -154808.68 0.59 0.08 0.28 0.05 0.23
## [7] 0.13 0.85 0.03 0.56 0.04
## [1] -154799.06 0.58 0.08 0.28 0.06 0.24
## [7] 0.13 0.85 0.03 0.56 0.04
## [1] 18
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -159623.23 0.58 0.17 0.23 0.02 0.17
## [7] 0.09 0.87 0.03 0.52 0.05
## [1] -156450.19 0.62 0.13 0.22 0.03 0.19
## [7] 0.10 0.86 0.03 0.53 0.05
## [1] -155855.67 0.64 0.11 0.22 0.03 0.21
## [7] 0.11 0.85 0.03 0.54 0.04
## [1] -155639.96 0.64 0.10 0.22 0.04 0.22
## [7] 0.11 0.84 0.04 0.55 0.04
## [1] -155563.14 0.64 0.10 0.22 0.04 0.23
## [7] 0.12 0.84 0.04 0.56 0.04
## [1] -155546.38 0.63 0.09 0.22 0.05 0.24
## [7] 0.12 0.84 0.04 0.56 0.04
## [1] -155554.75 0.63 0.09 0.23 0.05 0.25
## [7] 0.12 0.83 0.04 0.57 0.04
## [1] 19
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -158766.69 0.56 0.16 0.26 0.02 0.17
## [7] 0.09 0.87 0.03 0.52 0.05
## [1] -155660.29 0.60 0.12 0.26 0.02 0.19
## [7] 0.10 0.86 0.03 0.53 0.05
## [1] -155177.48 0.61 0.10 0.26 0.03 0.21
## [7] 0.11 0.85 0.03 0.54 0.04
## [1] -155006.79 0.61 0.09 0.26 0.04 0.22
## [7] 0.11 0.85 0.03 0.55 0.04
## [1] -154936.92 0.61 0.09 0.27 0.04 0.23
## [7] 0.12 0.85 0.03 0.55 0.04
## [1] -154910.18 0.60 0.08 0.27 0.05 0.24
## [7] 0.12 0.85 0.03 0.56 0.04
## [1] -154902.65 0.60 0.08 0.27 0.05 0.25
## [7] 0.13 0.85 0.03 0.56 0.04
## [1] 20
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -160347.69 0.59 0.18 0.21 0.02 0.16
## [7] 0.10 0.86 0.03 0.52 0.05
## [1] -156638.86 0.63 0.14 0.20 0.03 0.18
## [7] 0.10 0.84 0.03 0.53 0.05
## [1] -155906.57 0.64 0.13 0.21 0.03 0.19
## [7] 0.11 0.83 0.03 0.54 0.05
## [1] -155700.05 0.64 0.11 0.21 0.04 0.20
## [7] 0.11 0.82 0.03 0.55 0.05
## [1] -155659.56 0.64 0.11 0.21 0.04 0.21
## [7] 0.12 0.82 0.03 0.55 0.04
## [1] -155672.32 0.63 0.10 0.22 0.04 0.22
## [7] 0.12 0.82 0.04 0.56 0.04
## [1] -155698.02 0.63 0.10 0.22 0.05 0.22
## [7] 0.12 0.81 0.04 0.56 0.04
## [1] -155722.63 0.62 0.10 0.22 0.05 0.22
## [7] 0.13 0.81 0.04 0.56 0.04
## [1] -155741.70 0.62 0.10 0.23 0.05 0.23
## [7] 0.13 0.81 0.04 0.56 0.04
## [1] -155754.60 0.61 0.10 0.23 0.06 0.23
## [7] 0.13 0.81 0.04 0.56 0.04
## [1] -155762.12 0.61 0.10 0.23 0.06 0.23
## [7] 0.13 0.81 0.04 0.56 0.04
## [1] 21
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -160298.78 0.59 0.18 0.22 0.02 0.16
## [7] 0.09 0.86 0.03 0.52 0.05
## [1] -156358.44 0.62 0.14 0.21 0.03 0.18
## [7] 0.10 0.85 0.03 0.54 0.05
## [1] -155618.23 0.63 0.12 0.22 0.03 0.19
## [7] 0.10 0.83 0.03 0.55 0.04
## [1] -155404.35 0.63 0.11 0.22 0.04 0.20
## [7] 0.10 0.83 0.03 0.56 0.04
## [1] -155364.82 0.63 0.10 0.23 0.04 0.20
## [7] 0.10 0.82 0.04 0.57 0.04
## [1] -155386.14 0.62 0.10 0.23 0.05 0.20
## [7] 0.11 0.82 0.04 0.57 0.04
## [1] -155424.14 0.61 0.10 0.24 0.05 0.21
## [7] 0.11 0.82 0.04 0.58 0.04
## [1] -155461.56 0.61 0.10 0.24 0.06 0.21
## [7] 0.11 0.81 0.04 0.58 0.03
## [1] -155492.38 0.60 0.10 0.24 0.06 0.21
## [7] 0.11 0.81 0.04 0.58 0.03
## [1] -155515.34 0.59 0.10 0.25 0.06 0.21
## [7] 0.11 0.81 0.04 0.58 0.03
## [1] -155531.28 0.59 0.10 0.25 0.07 0.21
## [7] 0.11 0.81 0.04 0.58 0.03
## [1] -155541.21 0.58 0.10 0.25 0.07 0.21
## [7] 0.11 0.81 0.04 0.58 0.03
## [1] 22
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -160906.11 0.60 0.21 0.17 0.02 0.16
## [7] 0.09 0.86 0.04 0.52 0.05
## [1] -157247.64 0.65 0.18 0.15 0.03 0.18
## [7] 0.09 0.84 0.04 0.53 0.05
## [1] -156509.64 0.66 0.16 0.14 0.03 0.19
## [7] 0.09 0.83 0.04 0.54 0.04
## [1] -156270.59 0.67 0.15 0.14 0.04 0.19
## [7] 0.09 0.81 0.04 0.55 0.04
## [1] -156220.83 0.67 0.14 0.15 0.05 0.20
## [7] 0.09 0.81 0.04 0.55 0.04
## [1] -156243.75 0.66 0.14 0.15 0.05 0.20
## [7] 0.09 0.80 0.05 0.56 0.04
## [1] -156287.76 0.65 0.14 0.15 0.06 0.20
## [7] 0.09 0.79 0.05 0.56 0.04
## [1] -156330.65 0.65 0.14 0.15 0.06 0.20
## [7] 0.09 0.79 0.05 0.56 0.04
## [1] -156364.11 0.64 0.14 0.16 0.06 0.20
## [7] 0.09 0.79 0.05 0.56 0.04
## [1] -156386.42 0.64 0.14 0.16 0.07 0.20
## [7] 0.09 0.79 0.05 0.56 0.04
## [1] -156398.51 0.63 0.14 0.16 0.07 0.20
## [7] 0.09 0.79 0.05 0.56 0.04
## [1] -156402.50 0.62 0.14 0.16 0.07 0.20
## [7] 0.09 0.78 0.05 0.56 0.04
## [1] 23
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -160598.48 0.59 0.23 0.15 0.02 0.15
## [7] 0.09 0.86 0.03 0.52 0.05
## [1] -156829.70 0.63 0.20 0.13 0.03 0.16
## [7] 0.09 0.83 0.03 0.53 0.05
## [1] -156139.69 0.65 0.19 0.13 0.03 0.16
## [7] 0.09 0.82 0.03 0.54 0.04
## [1] -155951.36 0.65 0.18 0.13 0.04 0.17
## [7] 0.09 0.81 0.03 0.55 0.04
## [1] -155932.23 0.65 0.17 0.14 0.05 0.17
## [7] 0.09 0.80 0.03 0.55 0.04
## [1] -155969.62 0.64 0.17 0.14 0.05 0.16
## [7] 0.09 0.80 0.03 0.55 0.04
## [1] -156019.01 0.63 0.17 0.14 0.06 0.16
## [7] 0.09 0.79 0.03 0.55 0.04
## [1] -156062.89 0.62 0.17 0.14 0.06 0.16
## [7] 0.09 0.79 0.03 0.56 0.04
## [1] -156094.85 0.62 0.17 0.15 0.07 0.16
## [7] 0.09 0.79 0.03 0.56 0.04
## [1] -156114.03 0.61 0.17 0.15 0.07 0.16
## [7] 0.08 0.79 0.04 0.56 0.04
## [1] -156121.68 0.60 0.17 0.15 0.08 0.16
## [7] 0.08 0.79 0.04 0.56 0.04
## [1] 24
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -157324.85 0.52 0.32 0.14 0.02 0.13
## [7] 0.07 0.89 0.04 0.50 0.05
## [1] -155689.72 0.55 0.32 0.11 0.02 0.13
## [7] 0.07 0.89 0.04 0.50 0.04
## [1] -155671.43 0.56 0.32 0.09 0.03 0.13
## [7] 0.06 0.89 0.04 0.50 0.04
## [1] -155708.53 0.57 0.31 0.08 0.03 0.13
## [7] 0.06 0.89 0.04 0.49 0.04
## [1] -155747.70 0.58 0.30 0.08 0.04 0.13
## [7] 0.06 0.89 0.04 0.49 0.04
## [1] -155783.45 0.58 0.30 0.07 0.05 0.12
## [7] 0.05 0.90 0.04 0.49 0.04
## [1] -155814.94 0.59 0.29 0.07 0.05 0.12
## [7] 0.05 0.90 0.04 0.49 0.04
## [1] -155842.40 0.59 0.29 0.07 0.05 0.12
## [7] 0.05 0.90 0.04 0.48 0.04
## [1] -155864.93 0.59 0.29 0.07 0.06 0.11
## [7] 0.05 0.90 0.03 0.48 0.04
## [1] -155881.96 0.59 0.28 0.06 0.06 0.11
## [7] 0.04 0.91 0.03 0.48 0.04
## [1] -155894.36 0.59 0.28 0.06 0.07 0.11
## [7] 0.04 0.91 0.03 0.47 0.04
## [1] -155902.73 0.59 0.28 0.06 0.07 0.11
## [7] 0.04 0.91 0.03 0.47 0.04
## [1] 25
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -160447.86 0.60 0.27 0.11 0.02 0.15
## [7] 0.08 0.86 0.04 0.51 0.05
## [1] -157322.18 0.64 0.25 0.08 0.03 0.16
## [7] 0.08 0.84 0.04 0.52 0.04
## [1] -156700.27 0.65 0.24 0.07 0.04 0.16
## [7] 0.08 0.81 0.05 0.53 0.04
## [1] -156451.79 0.65 0.23 0.07 0.04 0.16
## [7] 0.08 0.80 0.05 0.53 0.04
## [1] -156373.45 0.65 0.23 0.07 0.05 0.16
## [7] 0.08 0.78 0.05 0.54 0.04
## [1] -156380.40 0.65 0.23 0.07 0.06 0.16
## [7] 0.08 0.77 0.05 0.54 0.04
## [1] 26
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -159355.88 0.57 0.25 0.15 0.02 0.15
## [7] 0.08 0.88 0.04 0.51 0.05
## [1] -157168.48 0.62 0.23 0.12 0.03 0.16
## [7] 0.08 0.86 0.05 0.52 0.04
## [1] -156853.78 0.64 0.22 0.11 0.03 0.16
## [7] 0.08 0.85 0.06 0.52 0.04
## [1] -156731.38 0.65 0.21 0.10 0.04 0.16
## [7] 0.08 0.84 0.06 0.52 0.04
## [1] -156678.48 0.65 0.20 0.10 0.04 0.16
## [7] 0.08 0.84 0.07 0.53 0.04
## [1] -156656.20 0.66 0.20 0.10 0.05 0.16
## [7] 0.08 0.83 0.07 0.53 0.04
## [1] -156647.03 0.66 0.19 0.10 0.05 0.16
## [7] 0.08 0.83 0.07 0.53 0.04
ggplot(sampleinfo_organoid_fetal, aes(as.numeric(as.character(passage.or.rescope.no_numeric)), thresholded_prior_ratio))+
geom_point(size=2,shape=21,color="black",aes(fill=as.factor(passage.or.rescope.no_numeric)))+xlab("Passage")+
ylab("Intermediate Peak Prior")+theme_bw()+theme(axis.title = element_text(size=12))+
#geom_text(aes(label=count, vjust=vjust, hjust=hjust), color="grey40", size=3)+
scale_x_continuous(breaks=c(1,2,3,4,6,7,8,2,4,10,11,14,16))+ scale_fill_manual(values=pass_col,name="Passage\nNumber", guide=F)
ggsave(here("figs","MTAB4957_fetal_mixture_model_ratio_maximize.pdf"), width=3, height=2)
sampleinfo_organoid_fetal$thresholded_ratio_max<-F
sampleinfo_organoid_fetal$thresholded_ratio_max[which(sampleinfo_organoid_fetal$thresholded_prior_ratio>1)]<-T
percent_passing<-round((tapply(sampleinfo_organoid_fetal$thresholded_ratio_max, sampleinfo_organoid_fetal$passage.or.rescope.no_numeric, sum)/tapply(sampleinfo_organoid_fetal$array.id, sampleinfo_organoid_fetal$passage.or.rescope.no_numeric, length))*100,2)
passed_num<-tapply(sampleinfo_organoid_fetal$thresholded_ratio_max, sampleinfo_organoid_fetal$passage.or.rescope.no_numeric, sum)
org_numer<-tapply(sampleinfo_organoid_fetal$array.id, sampleinfo_organoid_fetal$passage.or.rescope.no_numeric, length)
df<-data.frame(passage=names(percent_passing), passing=percent_passing, pro_passing=percent_passing/100, count=org_numer, passed_num=passed_num)
df$passage.factor <- factor(df$passage, levels = c(23,21,14,12,9,7,6,5,3,2,1))
df<-cbind(df,(binom.confint(df$passed_num, df$count, method="exact", conf.level=0.95)))
df$upper<-df$upper*100
df$lower<-df$lower*100
print(df)
## passage passing pro_passing count passed_num passage.factor method x n
## 1 1 0 0.0 4 0 1 exact 0 4
## 2 2 0 0.0 5 0 2 exact 0 5
## 3 3 0 0.0 3 0 3 exact 0 3
## 5 5 0 0.0 2 0 5 exact 0 2
## 6 6 0 0.0 2 0 6 exact 0 2
## 7 7 0 0.0 2 0 7 exact 0 2
## 9 9 0 0.0 2 0 9 exact 0 2
## 12 12 0 0.0 1 0 12 exact 0 1
## 14 14 50 0.5 2 1 14 exact 1 2
## 21 21 0 0.0 1 0 21 exact 0 1
## 23 23 0 0.0 2 0 23 exact 0 2
## mean lower upper
## 1 0.0 0.000000 60.23646
## 2 0.0 0.000000 52.18238
## 3 0.0 0.000000 70.75982
## 5 0.0 0.000000 84.18861
## 6 0.0 0.000000 84.18861
## 7 0.0 0.000000 84.18861
## 9 0.0 0.000000 84.18861
## 12 0.0 0.000000 97.50000
## 14 0.5 1.257912 98.74209
## 21 0.0 0.000000 97.50000
## 23 0.0 0.000000 84.18861
ggplot(df, aes(as.numeric(as.character(passage)), passing))+
geom_errorbar(aes(ymin=lower, ymax=upper), colour="grey70", width=.25)+
geom_line(color="grey20")+geom_point(size=1.25,shape=21,color="black",aes(fill=passage.factor))+xlab("Passage")+
ylab("Samples with Trimodal\nDistribution (%)")+theme_bw()+theme(axis.title = element_text(size=10))+
scale_x_continuous(breaks=c(1,2,3,4,6,7,8,2,4,10,11,14,16))+ scale_fill_manual(values=pass_col,name="Passage\nNumber", guide=F)
ggsave(here("figs","MTAB4957_fetal_mixture_model_ratio_threshold_maximize.pdf"), width=3, height=2)
## plot all samples
plts_paired<-lapply(1:nrow(sampleinfo_organoid_fetal), function(x){
print(x)
passage<-paste("passage: ",sampleinfo_organoid_fetal$passage.or.rescope.no_numeric[x],"\nIndividual: ", sampleinfo_organoid_fetal$Characteristics.individual.[x],"\nRatio I/H: " ,round(sampleinfo_organoid_fetal$thresholded_prior_ratio[x],2), sep="")
converted<-as.numeric(round(MTAB4957_beta_VeryVariable[,x]*1000,0))
counts<-rep(1000, length(converted))
res = em(converted, counts, .41, .31, .27, 0.01, .1, .1, .90, .03, .5, .05)
draw_fit_params_gg(converted, counts, res,passage)
})
## [1] 1
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -157952.80 0.56 0.28 0.14 0.02 0.14
## [7] 0.09 0.89 0.04 0.50 0.04
## [1] -156698.25 0.60 0.27 0.11 0.03 0.15
## [7] 0.09 0.88 0.04 0.50 0.04
## [1] -156685.93 0.62 0.26 0.09 0.04 0.15
## [7] 0.09 0.88 0.05 0.50 0.03
## [1] -156733.66 0.63 0.25 0.08 0.05 0.15
## [7] 0.09 0.88 0.05 0.50 0.03
## [1] -156784.92 0.63 0.24 0.07 0.05 0.15
## [7] 0.09 0.88 0.05 0.50 0.03
## [1] -156828.44 0.63 0.24 0.07 0.06 0.15
## [7] 0.09 0.88 0.05 0.50 0.03
## [1] -156863.15 0.63 0.24 0.06 0.07 0.15
## [7] 0.09 0.88 0.04 0.50 0.03
## [1] -156890.89 0.63 0.23 0.06 0.07 0.14
## [7] 0.08 0.88 0.04 0.50 0.03
## [1] -156912.20 0.63 0.23 0.06 0.08 0.14
## [7] 0.08 0.88 0.04 0.50 0.03
## [1] -156929.66 0.63 0.23 0.06 0.08 0.14
## [7] 0.08 0.89 0.04 0.50 0.03
## [1] -156944.50 0.63 0.23 0.06 0.09 0.14
## [7] 0.08 0.89 0.04 0.50 0.03
## [1] -156957.82 0.62 0.23 0.06 0.09 0.13
## [7] 0.07 0.89 0.04 0.50 0.03
## [1] -156970.26 0.62 0.22 0.06 0.09 0.13
## [7] 0.07 0.89 0.03 0.50 0.04
## [1] -156982.27 0.62 0.22 0.06 0.10 0.13
## [7] 0.07 0.89 0.03 0.50 0.04
## [1] -156994.24 0.62 0.22 0.06 0.10 0.13
## [7] 0.07 0.89 0.03 0.50 0.04
## [1] -157006.40 0.62 0.22 0.06 0.11 0.12
## [7] 0.07 0.90 0.03 0.49 0.04
## [1] -157018.95 0.62 0.22 0.06 0.11 0.12
## [7] 0.06 0.90 0.03 0.49 0.04
## [1] -157032.07 0.62 0.22 0.06 0.11 0.12
## [7] 0.06 0.90 0.03 0.49 0.04
## [1] -157046.11 0.61 0.21 0.06 0.12 0.12
## [7] 0.06 0.90 0.03 0.49 0.05
## [1] -157060.79 0.61 0.21 0.06 0.12 0.12
## [7] 0.06 0.90 0.03 0.49 0.05
## [1] -157076.20 0.61 0.21 0.06 0.12 0.11
## [7] 0.06 0.90 0.03 0.49 0.05
## [1] -157092.33 0.61 0.21 0.06 0.13 0.11
## [7] 0.05 0.90 0.02 0.48 0.05
## [1] -157109.19 0.61 0.21 0.06 0.13 0.11
## [7] 0.05 0.91 0.02 0.48 0.05
## [1] -157127.55 0.61 0.21 0.06 0.13 0.11
## [7] 0.05 0.91 0.02 0.48 0.06
## [1] -157146.52 0.61 0.20 0.06 0.13 0.11
## [7] 0.05 0.91 0.02 0.48 0.06
## [1] -157166.10 0.61 0.20 0.05 0.14 0.11
## [7] 0.05 0.91 0.02 0.48 0.06
## [1] -157186.25 0.60 0.20 0.05 0.14 0.10
## [7] 0.05 0.91 0.02 0.47 0.06
## [1] -157206.95 0.60 0.20 0.05 0.14 0.10
## [7] 0.04 0.91 0.02 0.47 0.06
## [1] -157228.14 0.60 0.20 0.05 0.15 0.10
## [7] 0.04 0.91 0.02 0.47 0.07
## [1] -157249.76 0.60 0.19 0.05 0.15 0.10
## [7] 0.04 0.91 0.02 0.47 0.07
## [1] -157271.76 0.60 0.19 0.05 0.15 0.10
## [7] 0.04 0.91 0.02 0.47 0.07
## [1] -157294.09 0.60 0.19 0.05 0.16 0.10
## [7] 0.04 0.91 0.02 0.46 0.07
## [1] -157316.67 0.60 0.19 0.05 0.16 0.09
## [7] 0.04 0.91 0.02 0.46 0.08
## [1] -157339.47 0.60 0.19 0.05 0.16 0.09
## [7] 0.04 0.91 0.02 0.46 0.08
## [1] -157362.41 0.59 0.19 0.05 0.17 0.09
## [7] 0.03 0.91 0.02 0.46 0.08
## [1] -157383.97 0.59 0.18 0.05 0.17 0.09
## [7] 0.03 0.91 0.02 0.46 0.08
## [1] -157405.81 0.59 0.18 0.05 0.17 0.09
## [7] 0.03 0.91 0.02 0.46 0.08
## [1] -157427.80 0.59 0.18 0.05 0.17 0.09
## [7] 0.03 0.91 0.02 0.45 0.09
## [1] -157449.85 0.59 0.18 0.05 0.18 0.09
## [7] 0.03 0.92 0.02 0.45 0.09
## [1] -157471.88 0.59 0.18 0.05 0.18 0.09
## [7] 0.03 0.92 0.02 0.45 0.09
## [1] -157493.85 0.59 0.18 0.05 0.18 0.09
## [7] 0.03 0.92 0.02 0.45 0.09
## [1] -157515.72 0.58 0.18 0.05 0.19 0.08
## [7] 0.03 0.92 0.02 0.45 0.10
## [1] -157537.45 0.58 0.18 0.05 0.19 0.08
## [7] 0.03 0.92 0.02 0.45 0.10
## [1] -157559.01 0.58 0.17 0.05 0.19 0.08
## [7] 0.03 0.92 0.02 0.45 0.10
## [1] -157580.39 0.58 0.17 0.05 0.19 0.08
## [7] 0.03 0.92 0.02 0.44 0.10
## [1] -157601.56 0.58 0.17 0.05 0.20 0.08
## [7] 0.03 0.92 0.02 0.44 0.10
## [1] -157622.51 0.58 0.17 0.05 0.20 0.08
## [7] 0.03 0.92 0.02 0.44 0.11
## [1] -157643.23 0.57 0.17 0.05 0.20 0.08
## [7] 0.03 0.92 0.02 0.44 0.11
## [1] -157663.67 0.57 0.17 0.05 0.21 0.08
## [7] 0.02 0.92 0.02 0.44 0.11
## [1] -157683.93 0.57 0.17 0.05 0.21 0.08
## [7] 0.02 0.92 0.02 0.44 0.11
## [1] -157703.91 0.57 0.17 0.05 0.21 0.08
## [7] 0.02 0.92 0.02 0.44 0.12
## [1] -157723.64 0.57 0.17 0.05 0.22 0.08
## [7] 0.02 0.92 0.02 0.44 0.12
## [1] -157743.11 0.56 0.16 0.05 0.22 0.08
## [7] 0.02 0.92 0.02 0.44 0.12
## [1] -157762.32 0.56 0.16 0.05 0.22 0.08
## [7] 0.02 0.92 0.02 0.43 0.12
## [1] -157781.27 0.56 0.16 0.05 0.22 0.08
## [7] 0.02 0.92 0.02 0.43 0.12
## [1] -157799.96 0.56 0.16 0.06 0.23 0.08
## [7] 0.02 0.92 0.02 0.43 0.13
## [1] -157818.40 0.55 0.16 0.06 0.23 0.07
## [7] 0.02 0.92 0.02 0.43 0.13
## [1] -157834.71 0.55 0.16 0.06 0.23 0.07
## [7] 0.02 0.92 0.02 0.43 0.13
## [1] -157851.11 0.55 0.16 0.06 0.24 0.07
## [7] 0.02 0.92 0.02 0.43 0.13
## [1] -157867.58 0.55 0.16 0.06 0.24 0.07
## [7] 0.02 0.92 0.02 0.43 0.13
## [1] -157884.01 0.54 0.16 0.06 0.24 0.07
## [7] 0.02 0.92 0.02 0.43 0.14
## [1] -157901.25 0.54 0.16 0.06 0.25 0.07
## [7] 0.02 0.92 0.02 0.43 0.14
## [1] -157917.48 0.54 0.16 0.06 0.25 0.07
## [7] 0.02 0.92 0.02 0.43 0.14
## [1] -157934.18 0.53 0.16 0.06 0.25 0.07
## [7] 0.02 0.92 0.02 0.43 0.14
## [1] -157950.71 0.53 0.16 0.06 0.26 0.07
## [7] 0.02 0.92 0.02 0.43 0.14
## [1] -157966.87 0.53 0.15 0.06 0.26 0.07
## [7] 0.02 0.92 0.02 0.43 0.15
## [1] -157982.65 0.53 0.15 0.06 0.26 0.07
## [7] 0.02 0.92 0.02 0.43 0.15
## [1] -157998.21 0.52 0.15 0.06 0.27 0.07
## [7] 0.02 0.92 0.02 0.43 0.15
## [1] -158013.41 0.52 0.15 0.06 0.27 0.07
## [7] 0.02 0.92 0.02 0.43 0.15
## [1] -158028.30 0.52 0.15 0.06 0.27 0.07
## [7] 0.02 0.92 0.02 0.43 0.15
## [1] -158042.86 0.51 0.15 0.06 0.28 0.07
## [7] 0.02 0.92 0.02 0.43 0.15
## [1] -158057.09 0.51 0.15 0.06 0.28 0.07
## [7] 0.02 0.92 0.02 0.43 0.16
## [1] -158070.99 0.51 0.15 0.06 0.28 0.07
## [7] 0.02 0.92 0.02 0.43 0.16
## [1] -158084.55 0.50 0.15 0.06 0.29 0.07
## [7] 0.02 0.92 0.02 0.43 0.16
## [1] -158097.78 0.50 0.15 0.06 0.29 0.07
## [7] 0.02 0.92 0.02 0.43 0.16
## [1] -158110.65 0.50 0.15 0.06 0.29 0.07
## [7] 0.02 0.92 0.02 0.43 0.16
## [1] -158123.16 0.49 0.15 0.06 0.30 0.07
## [7] 0.02 0.92 0.02 0.43 0.16
## [1] -158135.34 0.49 0.15 0.06 0.30 0.07
## [7] 0.02 0.92 0.02 0.43 0.16
## [1] -158147.16 0.49 0.15 0.06 0.30 0.07
## [7] 0.02 0.92 0.02 0.43 0.17
## [1] -158158.39 0.48 0.15 0.06 0.31 0.07
## [7] 0.02 0.92 0.02 0.43 0.17
## [1] -158169.94 0.48 0.15 0.06 0.31 0.07
## [7] 0.02 0.92 0.02 0.43 0.17
## [1] -158180.40 0.48 0.15 0.06 0.32 0.07
## [7] 0.02 0.92 0.02 0.43 0.17
## [1] -158191.34 0.47 0.15 0.06 0.32 0.07
## [7] 0.02 0.92 0.02 0.43 0.17
## [1] -158200.68 0.47 0.15 0.06 0.32 0.07
## [7] 0.02 0.92 0.02 0.43 0.17
## [1] 2
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -159957.90 0.58 0.16 0.24 0.02 0.17
## [7] 0.10 0.87 0.03 0.52 0.05
## [1] -156264.73 0.62 0.12 0.24 0.03 0.19
## [7] 0.11 0.85 0.03 0.54 0.05
## [1] -155514.48 0.62 0.10 0.25 0.03 0.21
## [7] 0.11 0.84 0.03 0.55 0.04
## [1] -155286.99 0.62 0.09 0.25 0.04 0.23
## [7] 0.12 0.83 0.03 0.56 0.04
## [1] -155230.55 0.62 0.08 0.26 0.04 0.24
## [7] 0.12 0.83 0.03 0.56 0.04
## [1] -155236.15 0.61 0.08 0.26 0.05 0.25
## [7] 0.13 0.83 0.04 0.57 0.04
## [1] 3
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -156851.65 0.52 0.33 0.14 0.02 0.13
## [7] 0.08 0.90 0.04 0.49 0.04
## [1] -155670.41 0.54 0.33 0.11 0.02 0.13
## [7] 0.08 0.90 0.04 0.49 0.04
## [1] -155746.33 0.56 0.32 0.09 0.03 0.13
## [7] 0.08 0.90 0.04 0.49 0.04
## [1] -155871.81 0.56 0.32 0.08 0.03 0.13
## [7] 0.08 0.91 0.04 0.48 0.03
## [1] -155999.20 0.57 0.31 0.08 0.04 0.13
## [7] 0.08 0.91 0.04 0.48 0.03
## [1] -156117.45 0.57 0.31 0.08 0.05 0.13
## [7] 0.07 0.91 0.03 0.48 0.03
## [1] -156221.30 0.57 0.31 0.07 0.05 0.13
## [7] 0.07 0.92 0.03 0.47 0.03
## [1] -156307.54 0.57 0.30 0.07 0.06 0.13
## [7] 0.07 0.92 0.03 0.47 0.03
## [1] -156375.50 0.57 0.30 0.07 0.06 0.12
## [7] 0.07 0.92 0.03 0.47 0.03
## [1] -156424.53 0.57 0.30 0.07 0.06 0.12
## [7] 0.07 0.92 0.02 0.47 0.03
## [1] -156456.09 0.57 0.30 0.07 0.07 0.12
## [7] 0.06 0.93 0.02 0.46 0.03
## [1] -156472.42 0.56 0.30 0.07 0.07 0.12
## [7] 0.06 0.93 0.02 0.46 0.03
## [1] -156474.93 0.56 0.29 0.07 0.08 0.12
## [7] 0.06 0.93 0.02 0.46 0.03
## [1] 4
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -155944.91 0.46 0.43 0.10 0.01 0.12
## [7] 0.06 0.89 0.04 0.48 0.05
## [1] -153982.54 0.45 0.47 0.07 0.01 0.12
## [7] 0.06 0.90 0.04 0.47 0.04
## [1] -153857.92 0.44 0.48 0.06 0.02 0.12
## [7] 0.06 0.90 0.04 0.46 0.04
## [1] -153888.03 0.44 0.49 0.05 0.02 0.12
## [7] 0.06 0.90 0.04 0.45 0.04
## [1] -153959.91 0.44 0.49 0.05 0.02 0.12
## [7] 0.06 0.91 0.03 0.45 0.04
## [1] -154040.24 0.44 0.49 0.04 0.03 0.12
## [7] 0.06 0.91 0.03 0.44 0.03
## [1] -154113.45 0.44 0.48 0.04 0.03 0.12
## [7] 0.06 0.91 0.03 0.43 0.03
## [1] -154171.74 0.44 0.48 0.04 0.03 0.12
## [7] 0.06 0.91 0.03 0.43 0.03
## [1] -154211.24 0.44 0.48 0.04 0.04 0.11
## [7] 0.06 0.92 0.02 0.42 0.03
## [1] -154230.92 0.44 0.48 0.04 0.04 0.11
## [7] 0.05 0.92 0.02 0.42 0.03
## [1] -154231.47 0.43 0.48 0.04 0.05 0.11
## [7] 0.05 0.92 0.02 0.42 0.03
## [1] 5
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -156833.58 0.51 0.39 0.09 0.02 0.12
## [7] 0.07 0.88 0.04 0.49 0.04
## [1] -155288.23 0.51 0.41 0.05 0.02 0.12
## [7] 0.07 0.88 0.04 0.48 0.04
## [1] -155206.60 0.52 0.42 0.04 0.03 0.12
## [7] 0.07 0.88 0.04 0.47 0.03
## [1] -155226.02 0.52 0.42 0.03 0.04 0.12
## [7] 0.07 0.88 0.04 0.46 0.03
## [1] -155267.09 0.52 0.41 0.02 0.04 0.12
## [7] 0.07 0.88 0.04 0.46 0.03
## [1] -155306.10 0.51 0.41 0.02 0.05 0.12
## [7] 0.07 0.88 0.04 0.45 0.03
## [1] -155334.58 0.51 0.41 0.02 0.06 0.12
## [7] 0.07 0.88 0.04 0.45 0.03
## [1] -155350.38 0.50 0.41 0.02 0.07 0.12
## [7] 0.06 0.88 0.04 0.45 0.03
## [1] -155354.20 0.50 0.41 0.02 0.08 0.12
## [7] 0.06 0.89 0.03 0.44 0.03
## [1] 6
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -157509.21 0.54 0.25 0.19 0.02 0.13
## [7] 0.09 0.88 0.04 0.51 0.04
## [1] -156289.32 0.59 0.22 0.17 0.03 0.13
## [7] 0.09 0.87 0.04 0.52 0.04
## [1] -156129.04 0.61 0.20 0.15 0.03 0.13
## [7] 0.08 0.87 0.05 0.53 0.04
## [1] -156091.06 0.62 0.19 0.15 0.04 0.13
## [7] 0.08 0.86 0.05 0.53 0.03
## [1] -156095.91 0.62 0.19 0.15 0.04 0.12
## [7] 0.08 0.86 0.05 0.53 0.03
## [1] 7
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -158735.16 0.57 0.29 0.11 0.02 0.13
## [7] 0.09 0.87 0.04 0.50 0.04
## [1] -157153.62 0.62 0.28 0.08 0.03 0.14
## [7] 0.09 0.86 0.05 0.51 0.04
## [1] -156846.37 0.63 0.27 0.06 0.04 0.15
## [7] 0.09 0.84 0.06 0.51 0.04
## [1] -156673.36 0.64 0.26 0.05 0.05 0.15
## [7] 0.10 0.83 0.06 0.51 0.04
## [1] -156555.97 0.64 0.25 0.05 0.06 0.15
## [7] 0.09 0.81 0.07 0.51 0.04
## [1] -156470.97 0.64 0.25 0.04 0.06 0.14
## [7] 0.09 0.80 0.07 0.51 0.03
## [1] -156406.80 0.64 0.25 0.04 0.07 0.14
## [7] 0.09 0.79 0.07 0.51 0.04
## [1] -156355.33 0.64 0.25 0.04 0.08 0.14
## [7] 0.09 0.78 0.07 0.51 0.04
## [1] -156311.68 0.63 0.25 0.04 0.08 0.14
## [7] 0.09 0.78 0.07 0.51 0.04
## [1] -156272.32 0.63 0.24 0.04 0.09 0.14
## [7] 0.08 0.77 0.08 0.51 0.04
## [1] -156234.85 0.63 0.24 0.04 0.09 0.13
## [7] 0.08 0.76 0.08 0.51 0.04
## [1] -156197.68 0.62 0.24 0.04 0.10 0.13
## [7] 0.08 0.76 0.08 0.50 0.04
## [1] -156159.84 0.62 0.24 0.04 0.10 0.13
## [7] 0.08 0.76 0.08 0.50 0.04
## [1] -156120.89 0.62 0.24 0.04 0.10 0.13
## [7] 0.07 0.75 0.08 0.50 0.04
## [1] -156080.77 0.61 0.24 0.04 0.11 0.12
## [7] 0.07 0.75 0.08 0.50 0.04
## [1] -156039.62 0.61 0.24 0.04 0.11 0.12
## [7] 0.07 0.75 0.08 0.50 0.05
## [1] -155997.75 0.61 0.23 0.04 0.12 0.12
## [7] 0.07 0.74 0.08 0.49 0.05
## [1] -155955.50 0.61 0.23 0.04 0.12 0.12
## [7] 0.07 0.74 0.08 0.49 0.05
## [1] -155913.25 0.60 0.23 0.04 0.12 0.11
## [7] 0.06 0.74 0.08 0.49 0.05
## [1] -155871.36 0.60 0.23 0.04 0.13 0.11
## [7] 0.06 0.74 0.08 0.48 0.05
## [1] -155830.18 0.60 0.23 0.04 0.13 0.11
## [7] 0.06 0.74 0.08 0.48 0.06
## [1] -155790.02 0.60 0.22 0.05 0.13 0.11
## [7] 0.06 0.74 0.08 0.48 0.06
## [1] -155751.15 0.60 0.22 0.05 0.14 0.11
## [7] 0.05 0.74 0.08 0.47 0.06
## [1] -155713.78 0.59 0.22 0.05 0.14 0.10
## [7] 0.05 0.74 0.08 0.47 0.06
## [1] -155678.12 0.59 0.22 0.05 0.14 0.10
## [7] 0.05 0.73 0.08 0.47 0.06
## [1] -155644.30 0.59 0.22 0.05 0.15 0.10
## [7] 0.05 0.73 0.08 0.47 0.06
## [1] -155612.46 0.59 0.21 0.05 0.15 0.10
## [7] 0.05 0.73 0.08 0.46 0.07
## [1] -155582.68 0.58 0.21 0.05 0.15 0.10
## [7] 0.05 0.73 0.08 0.46 0.07
## [1] -155555.02 0.58 0.21 0.05 0.16 0.09
## [7] 0.04 0.73 0.08 0.46 0.07
## [1] -155529.53 0.58 0.21 0.05 0.16 0.09
## [7] 0.04 0.73 0.08 0.45 0.07
## [1] -155506.18 0.58 0.21 0.05 0.16 0.09
## [7] 0.04 0.73 0.08 0.45 0.07
## [1] -155484.98 0.58 0.20 0.05 0.17 0.09
## [7] 0.04 0.73 0.08 0.45 0.08
## [1] -155465.90 0.57 0.20 0.05 0.17 0.09
## [7] 0.04 0.73 0.08 0.44 0.08
## [1] -155448.90 0.57 0.20 0.05 0.17 0.09
## [7] 0.04 0.73 0.08 0.44 0.08
## [1] -155433.91 0.57 0.20 0.05 0.18 0.08
## [7] 0.03 0.73 0.08 0.44 0.08
## [1] -155420.85 0.57 0.20 0.05 0.18 0.08
## [7] 0.03 0.73 0.08 0.44 0.08
## [1] -155409.65 0.57 0.19 0.05 0.18 0.08
## [7] 0.03 0.73 0.08 0.43 0.09
## [1] -155400.20 0.57 0.19 0.06 0.19 0.08
## [7] 0.03 0.73 0.08 0.43 0.09
## [1] 8
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -160911.83 0.60 0.22 0.16 0.02 0.15
## [7] 0.09 0.86 0.03 0.51 0.05
## [1] -157017.47 0.64 0.19 0.14 0.03 0.17
## [7] 0.09 0.83 0.03 0.53 0.05
## [1] -156265.90 0.66 0.17 0.14 0.03 0.18
## [7] 0.10 0.82 0.03 0.54 0.04
## [1] -156048.24 0.66 0.16 0.14 0.04 0.18
## [7] 0.10 0.81 0.03 0.54 0.04
## [1] -156013.35 0.66 0.16 0.14 0.05 0.18
## [7] 0.10 0.80 0.03 0.55 0.04
## [1] -156040.19 0.65 0.15 0.14 0.05 0.19
## [7] 0.10 0.79 0.03 0.55 0.04
## [1] -156080.95 0.64 0.15 0.15 0.06 0.19
## [7] 0.10 0.79 0.03 0.55 0.04
## [1] -156117.44 0.63 0.15 0.15 0.06 0.19
## [7] 0.10 0.79 0.04 0.55 0.04
## [1] -156143.41 0.63 0.15 0.15 0.07 0.19
## [7] 0.10 0.79 0.04 0.55 0.04
## [1] -156158.45 0.62 0.16 0.16 0.07 0.19
## [7] 0.10 0.79 0.04 0.55 0.04
## [1] -156163.92 0.61 0.16 0.16 0.07 0.19
## [7] 0.10 0.78 0.04 0.55 0.04
## [1] 9
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -161638.23 0.62 0.19 0.16 0.02 0.17
## [7] 0.09 0.85 0.03 0.51 0.05
## [1] -157142.69 0.67 0.16 0.14 0.03 0.20
## [7] 0.10 0.83 0.03 0.53 0.04
## [1] -156228.96 0.68 0.14 0.14 0.04 0.21
## [7] 0.10 0.82 0.03 0.54 0.04
## [1] -155950.29 0.68 0.13 0.14 0.05 0.22
## [7] 0.10 0.81 0.03 0.54 0.04
## [1] -155898.64 0.67 0.13 0.15 0.05 0.23
## [7] 0.11 0.80 0.03 0.55 0.04
## [1] -155929.48 0.66 0.13 0.15 0.06 0.24
## [7] 0.11 0.79 0.03 0.55 0.04
## [1] -155982.66 0.65 0.13 0.15 0.07 0.25
## [7] 0.11 0.79 0.03 0.55 0.04
## [1] -156033.41 0.64 0.13 0.16 0.07 0.25
## [7] 0.11 0.79 0.04 0.55 0.04
## [1] -156072.50 0.63 0.13 0.16 0.08 0.25
## [7] 0.11 0.78 0.04 0.56 0.04
## [1] -156098.63 0.62 0.14 0.16 0.08 0.25
## [7] 0.11 0.78 0.04 0.56 0.04
## [1] -156113.57 0.61 0.14 0.17 0.08 0.25
## [7] 0.11 0.78 0.04 0.56 0.04
## [1] -156119.65 0.60 0.14 0.17 0.09 0.26
## [7] 0.11 0.78 0.04 0.56 0.04
## [1] 10
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -159328.07 0.58 0.22 0.18 0.02 0.15
## [7] 0.09 0.88 0.04 0.51 0.05
## [1] -157205.70 0.63 0.19 0.16 0.03 0.16
## [7] 0.09 0.86 0.05 0.52 0.04
## [1] -156780.59 0.65 0.17 0.15 0.03 0.17
## [7] 0.10 0.85 0.05 0.53 0.04
## [1] -156623.68 0.66 0.15 0.15 0.04 0.17
## [7] 0.10 0.84 0.06 0.54 0.04
## [1] -156571.96 0.66 0.15 0.15 0.04 0.17
## [7] 0.10 0.83 0.06 0.54 0.04
## [1] -156564.38 0.66 0.14 0.15 0.05 0.17
## [7] 0.10 0.83 0.06 0.55 0.04
## [1] 11
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -159121.75 0.57 0.27 0.13 0.02 0.14
## [7] 0.08 0.88 0.04 0.51 0.04
## [1] -157128.16 0.62 0.25 0.10 0.03 0.15
## [7] 0.08 0.86 0.05 0.52 0.04
## [1] -156774.55 0.64 0.24 0.09 0.04 0.15
## [7] 0.08 0.84 0.06 0.52 0.04
## [1] -156614.88 0.65 0.23 0.08 0.04 0.15
## [7] 0.08 0.83 0.06 0.53 0.04
## [1] -156536.74 0.65 0.22 0.08 0.05 0.14
## [7] 0.08 0.82 0.07 0.53 0.04
## [1] -156500.39 0.65 0.22 0.07 0.06 0.14
## [7] 0.08 0.81 0.07 0.53 0.04
## [1] -156485.06 0.65 0.21 0.07 0.06 0.14
## [7] 0.07 0.80 0.07 0.53 0.04
## [1] -156478.36 0.65 0.21 0.07 0.07 0.14
## [7] 0.07 0.80 0.07 0.53 0.04
## [1] 12
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -158970.73 0.57 0.17 0.24 0.02 0.16
## [7] 0.09 0.87 0.03 0.52 0.05
## [1] -155942.14 0.60 0.14 0.24 0.02 0.18
## [7] 0.10 0.86 0.03 0.53 0.05
## [1] -155480.73 0.61 0.12 0.24 0.03 0.19
## [7] 0.10 0.85 0.03 0.54 0.04
## [1] -155333.87 0.62 0.11 0.24 0.04 0.20
## [7] 0.10 0.85 0.03 0.55 0.04
## [1] -155281.81 0.62 0.10 0.24 0.04 0.21
## [7] 0.11 0.85 0.03 0.56 0.04
## [1] -155266.11 0.61 0.10 0.24 0.05 0.21
## [7] 0.11 0.84 0.03 0.56 0.04
## [1] -155264.73 0.61 0.10 0.24 0.05 0.21
## [7] 0.11 0.84 0.03 0.56 0.04
## [1] 13
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -160493.51 0.60 0.20 0.18 0.02 0.16
## [7] 0.09 0.86 0.03 0.52 0.05
## [1] -156901.58 0.64 0.16 0.17 0.03 0.18
## [7] 0.10 0.84 0.03 0.53 0.04
## [1] -156246.35 0.66 0.14 0.16 0.04 0.19
## [7] 0.10 0.83 0.03 0.54 0.04
## [1] -156042.13 0.66 0.13 0.16 0.04 0.20
## [7] 0.11 0.82 0.03 0.54 0.04
## [1] -155991.69 0.66 0.13 0.16 0.05 0.21
## [7] 0.11 0.82 0.04 0.55 0.04
## [1] -155998.34 0.65 0.12 0.17 0.06 0.21
## [7] 0.11 0.81 0.04 0.55 0.04
## [1] 14
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -157985.66 0.55 0.15 0.29 0.02 0.17
## [7] 0.09 0.88 0.03 0.52 0.05
## [1] -155298.48 0.57 0.11 0.29 0.02 0.19
## [7] 0.10 0.87 0.03 0.53 0.05
## [1] -154875.77 0.58 0.09 0.30 0.03 0.21
## [7] 0.10 0.86 0.03 0.54 0.04
## [1] -154731.59 0.58 0.08 0.30 0.03 0.22
## [7] 0.11 0.86 0.03 0.55 0.04
## [1] -154675.01 0.58 0.08 0.30 0.04 0.23
## [7] 0.11 0.86 0.03 0.55 0.04
## [1] -154653.48 0.58 0.07 0.30 0.04 0.24
## [7] 0.11 0.85 0.03 0.56 0.04
## [1] -154646.39 0.58 0.07 0.31 0.05 0.24
## [7] 0.12 0.85 0.04 0.56 0.04
## [1] 15
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -160561.43 0.60 0.20 0.18 0.02 0.16
## [7] 0.09 0.86 0.03 0.51 0.05
## [1] -156955.27 0.64 0.17 0.17 0.03 0.18
## [7] 0.09 0.84 0.03 0.52 0.05
## [1] -156310.09 0.65 0.15 0.16 0.03 0.20
## [7] 0.10 0.83 0.04 0.53 0.04
## [1] -156116.99 0.66 0.14 0.16 0.04 0.21
## [7] 0.10 0.82 0.04 0.54 0.04
## [1] -156074.73 0.66 0.13 0.17 0.04 0.21
## [7] 0.11 0.82 0.04 0.54 0.04
## [1] -156085.66 0.65 0.13 0.17 0.05 0.22
## [7] 0.11 0.81 0.04 0.55 0.04
## [1] -156111.46 0.65 0.13 0.17 0.05 0.22
## [7] 0.11 0.81 0.04 0.55 0.04
## [1] -156137.18 0.64 0.13 0.17 0.06 0.22
## [7] 0.11 0.81 0.04 0.55 0.04
## [1] -156157.47 0.63 0.13 0.17 0.06 0.22
## [7] 0.11 0.81 0.04 0.55 0.04
## [1] -156171.15 0.63 0.13 0.18 0.06 0.22
## [7] 0.11 0.81 0.04 0.55 0.04
## [1] -156179.01 0.62 0.13 0.18 0.07 0.23
## [7] 0.11 0.81 0.04 0.55 0.04
## [1] 16
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -158513.30 0.55 0.18 0.25 0.02 0.16
## [7] 0.09 0.87 0.03 0.52 0.05
## [1] -155719.03 0.59 0.15 0.24 0.02 0.17
## [7] 0.10 0.86 0.03 0.53 0.05
## [1] -155339.86 0.60 0.13 0.24 0.03 0.18
## [7] 0.10 0.86 0.03 0.54 0.05
## [1] -155213.01 0.61 0.12 0.24 0.03 0.19
## [7] 0.10 0.85 0.03 0.55 0.04
## [1] -155159.48 0.61 0.11 0.24 0.04 0.19
## [7] 0.10 0.85 0.03 0.55 0.04
## [1] -155135.64 0.60 0.11 0.24 0.04 0.20
## [7] 0.11 0.85 0.03 0.56 0.04
## [1] -155125.08 0.60 0.11 0.25 0.05 0.20
## [7] 0.11 0.85 0.03 0.56 0.04
## [1] -155120.02 0.60 0.11 0.25 0.05 0.20
## [7] 0.11 0.85 0.03 0.57 0.04
## [1] 17
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -158305.37 0.55 0.16 0.27 0.02 0.16
## [7] 0.09 0.87 0.03 0.52 0.05
## [1] -155471.42 0.58 0.12 0.27 0.02 0.18
## [7] 0.10 0.86 0.03 0.53 0.05
## [1] -155064.01 0.60 0.11 0.27 0.03 0.20
## [7] 0.11 0.86 0.03 0.54 0.04
## [1] -154924.29 0.60 0.10 0.27 0.03 0.21
## [7] 0.11 0.85 0.03 0.54 0.04
## [1] -154863.56 0.60 0.09 0.27 0.04 0.22
## [7] 0.12 0.85 0.03 0.55 0.04
## [1] -154834.50 0.60 0.09 0.27 0.04 0.22
## [7] 0.12 0.85 0.03 0.55 0.04
## [1] -154819.06 0.59 0.08 0.28 0.05 0.23
## [7] 0.12 0.85 0.03 0.56 0.04
## [1] -154808.68 0.59 0.08 0.28 0.05 0.23
## [7] 0.13 0.85 0.03 0.56 0.04
## [1] -154799.06 0.58 0.08 0.28 0.06 0.24
## [7] 0.13 0.85 0.03 0.56 0.04
## [1] 18
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -159623.23 0.58 0.17 0.23 0.02 0.17
## [7] 0.09 0.87 0.03 0.52 0.05
## [1] -156450.19 0.62 0.13 0.22 0.03 0.19
## [7] 0.10 0.86 0.03 0.53 0.05
## [1] -155855.67 0.64 0.11 0.22 0.03 0.21
## [7] 0.11 0.85 0.03 0.54 0.04
## [1] -155639.96 0.64 0.10 0.22 0.04 0.22
## [7] 0.11 0.84 0.04 0.55 0.04
## [1] -155563.14 0.64 0.10 0.22 0.04 0.23
## [7] 0.12 0.84 0.04 0.56 0.04
## [1] -155546.38 0.63 0.09 0.22 0.05 0.24
## [7] 0.12 0.84 0.04 0.56 0.04
## [1] -155554.75 0.63 0.09 0.23 0.05 0.25
## [7] 0.12 0.83 0.04 0.57 0.04
## [1] 19
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -158766.69 0.56 0.16 0.26 0.02 0.17
## [7] 0.09 0.87 0.03 0.52 0.05
## [1] -155660.29 0.60 0.12 0.26 0.02 0.19
## [7] 0.10 0.86 0.03 0.53 0.05
## [1] -155177.48 0.61 0.10 0.26 0.03 0.21
## [7] 0.11 0.85 0.03 0.54 0.04
## [1] -155006.79 0.61 0.09 0.26 0.04 0.22
## [7] 0.11 0.85 0.03 0.55 0.04
## [1] -154936.92 0.61 0.09 0.27 0.04 0.23
## [7] 0.12 0.85 0.03 0.55 0.04
## [1] -154910.18 0.60 0.08 0.27 0.05 0.24
## [7] 0.12 0.85 0.03 0.56 0.04
## [1] -154902.65 0.60 0.08 0.27 0.05 0.25
## [7] 0.13 0.85 0.03 0.56 0.04
## [1] 20
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -160347.69 0.59 0.18 0.21 0.02 0.16
## [7] 0.10 0.86 0.03 0.52 0.05
## [1] -156638.86 0.63 0.14 0.20 0.03 0.18
## [7] 0.10 0.84 0.03 0.53 0.05
## [1] -155906.57 0.64 0.13 0.21 0.03 0.19
## [7] 0.11 0.83 0.03 0.54 0.05
## [1] -155700.05 0.64 0.11 0.21 0.04 0.20
## [7] 0.11 0.82 0.03 0.55 0.05
## [1] -155659.56 0.64 0.11 0.21 0.04 0.21
## [7] 0.12 0.82 0.03 0.55 0.04
## [1] -155672.32 0.63 0.10 0.22 0.04 0.22
## [7] 0.12 0.82 0.04 0.56 0.04
## [1] -155698.02 0.63 0.10 0.22 0.05 0.22
## [7] 0.12 0.81 0.04 0.56 0.04
## [1] -155722.63 0.62 0.10 0.22 0.05 0.22
## [7] 0.13 0.81 0.04 0.56 0.04
## [1] -155741.70 0.62 0.10 0.23 0.05 0.23
## [7] 0.13 0.81 0.04 0.56 0.04
## [1] -155754.60 0.61 0.10 0.23 0.06 0.23
## [7] 0.13 0.81 0.04 0.56 0.04
## [1] -155762.12 0.61 0.10 0.23 0.06 0.23
## [7] 0.13 0.81 0.04 0.56 0.04
## [1] 21
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -160298.78 0.59 0.18 0.22 0.02 0.16
## [7] 0.09 0.86 0.03 0.52 0.05
## [1] -156358.44 0.62 0.14 0.21 0.03 0.18
## [7] 0.10 0.85 0.03 0.54 0.05
## [1] -155618.23 0.63 0.12 0.22 0.03 0.19
## [7] 0.10 0.83 0.03 0.55 0.04
## [1] -155404.35 0.63 0.11 0.22 0.04 0.20
## [7] 0.10 0.83 0.03 0.56 0.04
## [1] -155364.82 0.63 0.10 0.23 0.04 0.20
## [7] 0.10 0.82 0.04 0.57 0.04
## [1] -155386.14 0.62 0.10 0.23 0.05 0.20
## [7] 0.11 0.82 0.04 0.57 0.04
## [1] -155424.14 0.61 0.10 0.24 0.05 0.21
## [7] 0.11 0.82 0.04 0.58 0.04
## [1] -155461.56 0.61 0.10 0.24 0.06 0.21
## [7] 0.11 0.81 0.04 0.58 0.03
## [1] -155492.38 0.60 0.10 0.24 0.06 0.21
## [7] 0.11 0.81 0.04 0.58 0.03
## [1] -155515.34 0.59 0.10 0.25 0.06 0.21
## [7] 0.11 0.81 0.04 0.58 0.03
## [1] -155531.28 0.59 0.10 0.25 0.07 0.21
## [7] 0.11 0.81 0.04 0.58 0.03
## [1] -155541.21 0.58 0.10 0.25 0.07 0.21
## [7] 0.11 0.81 0.04 0.58 0.03
## [1] 22
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -160906.11 0.60 0.21 0.17 0.02 0.16
## [7] 0.09 0.86 0.04 0.52 0.05
## [1] -157247.64 0.65 0.18 0.15 0.03 0.18
## [7] 0.09 0.84 0.04 0.53 0.05
## [1] -156509.64 0.66 0.16 0.14 0.03 0.19
## [7] 0.09 0.83 0.04 0.54 0.04
## [1] -156270.59 0.67 0.15 0.14 0.04 0.19
## [7] 0.09 0.81 0.04 0.55 0.04
## [1] -156220.83 0.67 0.14 0.15 0.05 0.20
## [7] 0.09 0.81 0.04 0.55 0.04
## [1] -156243.75 0.66 0.14 0.15 0.05 0.20
## [7] 0.09 0.80 0.05 0.56 0.04
## [1] -156287.76 0.65 0.14 0.15 0.06 0.20
## [7] 0.09 0.79 0.05 0.56 0.04
## [1] -156330.65 0.65 0.14 0.15 0.06 0.20
## [7] 0.09 0.79 0.05 0.56 0.04
## [1] -156364.11 0.64 0.14 0.16 0.06 0.20
## [7] 0.09 0.79 0.05 0.56 0.04
## [1] -156386.42 0.64 0.14 0.16 0.07 0.20
## [7] 0.09 0.79 0.05 0.56 0.04
## [1] -156398.51 0.63 0.14 0.16 0.07 0.20
## [7] 0.09 0.79 0.05 0.56 0.04
## [1] -156402.50 0.62 0.14 0.16 0.07 0.20
## [7] 0.09 0.78 0.05 0.56 0.04
## [1] 23
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -160598.48 0.59 0.23 0.15 0.02 0.15
## [7] 0.09 0.86 0.03 0.52 0.05
## [1] -156829.70 0.63 0.20 0.13 0.03 0.16
## [7] 0.09 0.83 0.03 0.53 0.05
## [1] -156139.69 0.65 0.19 0.13 0.03 0.16
## [7] 0.09 0.82 0.03 0.54 0.04
## [1] -155951.36 0.65 0.18 0.13 0.04 0.17
## [7] 0.09 0.81 0.03 0.55 0.04
## [1] -155932.23 0.65 0.17 0.14 0.05 0.17
## [7] 0.09 0.80 0.03 0.55 0.04
## [1] -155969.62 0.64 0.17 0.14 0.05 0.16
## [7] 0.09 0.80 0.03 0.55 0.04
## [1] -156019.01 0.63 0.17 0.14 0.06 0.16
## [7] 0.09 0.79 0.03 0.55 0.04
## [1] -156062.89 0.62 0.17 0.14 0.06 0.16
## [7] 0.09 0.79 0.03 0.56 0.04
## [1] -156094.85 0.62 0.17 0.15 0.07 0.16
## [7] 0.09 0.79 0.03 0.56 0.04
## [1] -156114.03 0.61 0.17 0.15 0.07 0.16
## [7] 0.08 0.79 0.04 0.56 0.04
## [1] -156121.68 0.60 0.17 0.15 0.08 0.16
## [7] 0.08 0.79 0.04 0.56 0.04
## [1] 24
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -157324.85 0.52 0.32 0.14 0.02 0.13
## [7] 0.07 0.89 0.04 0.50 0.05
## [1] -155689.72 0.55 0.32 0.11 0.02 0.13
## [7] 0.07 0.89 0.04 0.50 0.04
## [1] -155671.43 0.56 0.32 0.09 0.03 0.13
## [7] 0.06 0.89 0.04 0.50 0.04
## [1] -155708.53 0.57 0.31 0.08 0.03 0.13
## [7] 0.06 0.89 0.04 0.49 0.04
## [1] -155747.70 0.58 0.30 0.08 0.04 0.13
## [7] 0.06 0.89 0.04 0.49 0.04
## [1] -155783.45 0.58 0.30 0.07 0.05 0.12
## [7] 0.05 0.90 0.04 0.49 0.04
## [1] -155814.94 0.59 0.29 0.07 0.05 0.12
## [7] 0.05 0.90 0.04 0.49 0.04
## [1] -155842.40 0.59 0.29 0.07 0.05 0.12
## [7] 0.05 0.90 0.04 0.48 0.04
## [1] -155864.93 0.59 0.29 0.07 0.06 0.11
## [7] 0.05 0.90 0.03 0.48 0.04
## [1] -155881.96 0.59 0.28 0.06 0.06 0.11
## [7] 0.04 0.91 0.03 0.48 0.04
## [1] -155894.36 0.59 0.28 0.06 0.07 0.11
## [7] 0.04 0.91 0.03 0.47 0.04
## [1] -155902.73 0.59 0.28 0.06 0.07 0.11
## [7] 0.04 0.91 0.03 0.47 0.04
## [1] 25
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -160447.86 0.60 0.27 0.11 0.02 0.15
## [7] 0.08 0.86 0.04 0.51 0.05
## [1] -157322.18 0.64 0.25 0.08 0.03 0.16
## [7] 0.08 0.84 0.04 0.52 0.04
## [1] -156700.27 0.65 0.24 0.07 0.04 0.16
## [7] 0.08 0.81 0.05 0.53 0.04
## [1] -156451.79 0.65 0.23 0.07 0.04 0.16
## [7] 0.08 0.80 0.05 0.53 0.04
## [1] -156373.45 0.65 0.23 0.07 0.05 0.16
## [7] 0.08 0.78 0.05 0.54 0.04
## [1] -156380.40 0.65 0.23 0.07 0.06 0.16
## [7] 0.08 0.77 0.05 0.54 0.04
## [1] 26
## [1] "loglik" "Prior(H)" "Prior(U)" "Prior(M)" "Prior(I)" "Mu(U)"
## [7] "Rho(U)" "MU(M)" "Rho(M)" "mu_I" "rho_I"
## [1] "XXX" "0.41" "0.31" "0.27" "0.01" "0.1" "0.1" "0.9" "0.03" "0.5"
## [11] "0.05"
## [1] -159355.88 0.57 0.25 0.15 0.02 0.15
## [7] 0.08 0.88 0.04 0.51 0.05
## [1] -157168.48 0.62 0.23 0.12 0.03 0.16
## [7] 0.08 0.86 0.05 0.52 0.04
## [1] -156853.78 0.64 0.22 0.11 0.03 0.16
## [7] 0.08 0.85 0.06 0.52 0.04
## [1] -156731.38 0.65 0.21 0.10 0.04 0.16
## [7] 0.08 0.84 0.06 0.52 0.04
## [1] -156678.48 0.65 0.20 0.10 0.04 0.16
## [7] 0.08 0.84 0.07 0.53 0.04
## [1] -156656.20 0.66 0.20 0.10 0.05 0.16
## [7] 0.08 0.83 0.07 0.53 0.04
## [1] -156647.03 0.66 0.19 0.10 0.05 0.16
## [7] 0.08 0.83 0.07 0.53 0.04
plts_paired_order<-plts_paired[order(sampleinfo_organoid_fetal$passage.or.rescope.no_numeric)]
pdf(here("figs","MTAB4957_fetal_organoids_thresholding_all_samples.pdf"))
plts_paired_order
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dev.off()
## png
## 2
mod<-model.matrix(~ 0 + passage.or.rescope.no_numeric, data=sampleinfo_organoid_notfetal)
fit <- lmFit(MTAB_organoid_beta_notfetal, mod)
ebfit <- eBayes(fit)
# covariate adjusted beta values
beta<-MTAB_organoid_beta_notfetal
passage_db<-sapply(1:nrow(beta), function(x){
sampleinfo_cpg<-sampleinfo_organoid_notfetal
sampleinfo_cpg$beta<-as.numeric(beta[x,])
fit<-lm(beta ~ passage.or.rescope.no_numeric, data=sampleinfo_cpg)
pval<-summary(fit)$coef["passage.or.rescope.no_numeric","Pr(>|t|)"]
slope<-fit$coefficients[2]
(min(sampleinfo_organoid_notfetal$passage.or.rescope.no_numeric)*slope) - (max(sampleinfo_organoid_notfetal$passage.or.rescope.no_numeric)*slope)})
passage_MTAB<-data.frame(p.value=ebfit$p.value[,"passage.or.rescope.no_numeric"], CpG=rownames(beta), db=passage_db)
# Adjust P values
passage_MTAB$p_adjusted<-p.adjust(passage_MTAB$p.value, method="BH")
diff_CpG_dbMTAB<-passage_MTAB[which(passage_MTAB$p_adjusted<0.05 & abs(passage_MTAB$db)>0.15),] #25086
diff_CpG_db_hypoMTAB<-diff_CpG_dbMTAB$CpG[which((diff_CpG_dbMTAB$db)>=0.15)] # 17419
diff_CpG_db_hyperMTAB<-diff_CpG_dbMTAB$CpG[which((diff_CpG_dbMTAB$db)<=(-0.15))] # 7667
load(here("data","beta_organoids.RData"))
pvals_long<-read.csv(here("data","Heteroskedactiy_pvalues_FDR_1000iter.csv"), header=T)
pvals_long[,1]<-NULL
colnames(pvals_long)<-c("BP_count","diff_count","mean_db","fdr_BP","fdr_diff")
pvals_long$CpG<-rownames(organoid_beta)
pvals_long$BP_pval<-((1000-pvals_long$BP_count)+1)/1001
pvals_long$diff_pval<-((1000-pvals_long$diff_count)+1)/1001
pvals_long$BP_fdr<-((1000-pvals_long$fdr_BP)+1)/1001
pvals_long$diff_fdr<-((1000-pvals_long$fdr_diff)+1)/1001
hetero_CpG<-rownames(organoid_beta)[which(pvals_long$BP_fdr<0.05)]
print(paste("CpGs with significant (adjusted p<0.05) heteroskedactiy: ", length(hetero_CpG), sep=""))
## [1] "CpGs with significant (adjusted p<0.05) heteroskedactiy: 41852"
diff_CpG<-rownames(organoid_beta)[which(pvals_long$diff_fdr<0.05)]
diff_CpG_db<-pvals_long[which(pvals_long$diff_fdr<0.05 & abs(pvals_long$mean_db)>0.15),]
print(paste("CpGs with significant (adjusted p<0.05; delta beta >0.05) differential methylation: ", nrow(diff_CpG_db), sep=""))
## [1] "CpGs with significant (adjusted p<0.05; delta beta >0.05) differential methylation: 23766"
diff_CpG_db_hypo<-diff_CpG_db$CpG[which((diff_CpG_db$mean_db)>=0.15)] # 11772
diff_CpG_db_hyper<-diff_CpG_db$CpG[which((diff_CpG_db$mean_db)<=(-0.15))] # 5214
How many differential CpGs could overlap? 450K vs EPIC
print(paste("Of the ", nrow(diff_CpG_db), " CpGs differential with passage in the original organoids, ",
length(diff_CpG_db$CpG[which(diff_CpG_db$CpG%in%rownames(MTAB_organoid_beta_notfetal))]), " are in the 450K data", sep=""))
## [1] "Of the 23766 CpGs differential with passage in the original organoids, 7628 are in the 450K data"
diff_CpG_db_hypo_overlap<-diff_CpG_db_hypo[which(diff_CpG_db_hypo%in%rownames(MTAB_organoid_beta_notfetal))]
diff_CpG_db_hyper_overlap<-diff_CpG_db_hyper[which(diff_CpG_db_hyper%in%rownames(MTAB_organoid_beta_notfetal))]
diff_CpG_db_hypoMTAB_overlap<-diff_CpG_db_hypoMTAB[which(diff_CpG_db_hypoMTAB%in%pvals_long$CpG)]
diff_CpG_db_hyperMTAB_overlap<-diff_CpG_db_hyperMTAB[which(diff_CpG_db_hyperMTAB%in%pvals_long$CpG)]
print(paste("Of the ",length(diff_CpG_db_hypo_overlap)," hypo CpGs also on the 450K ",
length(intersect(diff_CpG_db_hypoMTAB_overlap, diff_CpG_db_hypo_overlap))," are also hypo in the MTAB-4957 cohort (",
round((length(intersect(diff_CpG_db_hypoMTAB_overlap, diff_CpG_db_hypo_overlap))/length(diff_CpG_db_hypo_overlap))*100,2),"%)",sep=""))
## [1] "Of the 5098 hypo CpGs also on the 450K 3550 are also hypo in the MTAB-4957 cohort (69.64%)"
print(paste("Of the ",length(diff_CpG_db_hyper_overlap)," hyper CpGs also on the 450K ",
length(intersect(diff_CpG_db_hyperMTAB_overlap, diff_CpG_db_hyper_overlap))," are also hypo in the MTAB-4957 cohort (",
round((length(intersect(diff_CpG_db_hyperMTAB_overlap, diff_CpG_db_hyper_overlap))/length(diff_CpG_db_hyper_overlap))*100,2),"%)",sep=""))
## [1] "Of the 2530 hyper CpGs also on the 450K 1198 are also hypo in the MTAB-4957 cohort (47.35%)"
plt_db_direction<-merge(pvals_long[,c(3,6)], passage_MTAB, by="CpG")# 380776
plt_db_direction$sig<-"Not Significant"
plt_db_direction$sig[which(plt_db_direction$CpG%in%c(intersect(diff_CpG_db_hypoMTAB_overlap, diff_CpG_db_hypo_overlap),intersect(diff_CpG_db_hyperMTAB_overlap, diff_CpG_db_hyper_overlap)))]<-"Significant\nIn Both\nCohorts"
ggplot(plt_db_direction, aes(mean_db, db))+geom_point(aes(color=sig, alpha=sig),shape=19)+th+theme_bw()+
scale_color_manual(values=c("lightgrey", "cornflowerblue"), name="Significant\nWith Passage")+
scale_alpha_manual(values=c(0.25,1), guide=F)+
geom_hline(yintercept=c(-0.15,0.15), color="grey60")+geom_vline(xintercept=c(-0.15,0.15), color="grey60")+
ylim(-0.8,0.8)+xlim(-0.8,0.8)+xlab("Cohort 1\nPassage Delta Beta")+ylab("Cohort 2 Organoid\nPassage Delta Beta")+
stat_smooth(method="lm", se=F, color="black")
## Warning: Removed 1 rows containing non-finite values (stat_smooth).
## Warning: Removed 1 rows containing missing values (geom_point).
#ggsave(here("figs","MTAB_db_directionality.pdf"), width=5, height=3.75)
ggsave(here("figs/jpeg","MTAB_db_directionality.jpeg"), width=5, height=3.75)
## Warning: Removed 1 rows containing non-finite values (stat_smooth).
## Warning: Removed 1 rows containing missing values (geom_point).
print(paste("Correlation of delta betas between cohorts: ", round(cor(plt_db_direction$db, plt_db_direction$mean_db),2), sep=""))
## [1] "Correlation of delta betas between cohorts: 0.53"
epic.organoid_minimal<-epic.organoid[,c(2, 14, 17)]
colnames(epic.organoid_minimal)[1]<-"Assay.Name"
epic.organoid_minimal$cohort<-"Cohort 1 Organoids"
sampleinfo_organoid_notfetal_minimal<-sampleinfo_organoid_notfetal[,c(16,22,21)]
sampleinfo_organoid_notfetal_minimal$cohort<-"Cohort 2 Organoids"
sample_info_both<-rbind(sampleinfo_organoid_notfetal_minimal,epic.organoid_minimal)
plt_hetero_MTAB<-function(CpGs, legend, axislab, title){
betas<-melt(cbind(MTAB_organoid_beta_notfetal[CpGs,],organoid_beta[CpGs,]))
organoid_plt<-merge(sample_info_both, betas, by.x="Assay.Name",by.y="Var2")
p<-ggplot(organoid_plt, aes(passage.or.rescope.no_numeric,value))+
geom_line(aes(group=sample_ID),color="lightgrey")+
stat_smooth(method="lm", color="grey30", size=0.7, se=F)+th+theme_bw()+
geom_point(aes(fill=as.factor(passage.or.rescope.no_numeric)),shape=21, size=1.25)+
scale_fill_manual(values=pass_col,name="Passage\nNumber", drop=T)+
facet_grid(cohort~Var1)+
ylab("DNAm Beta")+xlab("Passage Number")+ylim(0,1)+
theme(plot.margin = margin(0.5, 0.15, 0.5, 0.15, "cm"),plot.title = element_text(size=12))+
xlim(1,16)
if(missing(legend) & missing(axislab) & missing(title)){p}else{
if(legend=="N" & axislab=="N"){p + theme(legend.position = "none",axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())+ ggtitle(title)}else{
if(legend=="N" & axislab=="Y"){p + theme(legend.position = "none") + ggtitle(title)}}}}
plt_hetero_MTAB(c("cg25402228","cg09146328"))
ggsave(here("figs","Passage_differential_CpGs_MTAB4957.pdf"),width = 4.75, height = 4)
ggsave(here("figs/jpeg","Passage_differential_CpGs_MTAB4957.jpeg"), width = 4.75, height = 4)
mod<-model.matrix(~ 0 + passage.or.rescope.no_numeric, data=sampleinfo_organoid_fetal)
fit <- lmFit(MTAB_organoid_beta_fetal, mod)
ebfit <- eBayes(fit)
# covariate adjusted beta values
beta<-MTAB_organoid_beta_fetal
passage_db<-sapply(1:nrow(beta), function(x){
sampleinfo_cpg<-sampleinfo_organoid_fetal
sampleinfo_cpg$beta<-as.numeric(beta[x,])
fit<-lm(beta ~ passage.or.rescope.no_numeric, data=sampleinfo_cpg)
pval<-summary(fit)$coef["passage.or.rescope.no_numeric","Pr(>|t|)"]
slope<-fit$coefficients[2]
(min(sampleinfo_organoid_fetal$passage.or.rescope.no_numeric)*slope) - (max(sampleinfo_organoid_fetal$passage.or.rescope.no_numeric)*slope)})
passage_MTAB<-data.frame(p.value=ebfit$p.value[,"passage.or.rescope.no_numeric"], CpG=rownames(beta), db=passage_db)
# p adjust
passage_MTAB$p_adjusted<-p.adjust(passage_MTAB$p.value, method="BH")
diff_CpG_dbMTAB<-passage_MTAB[which(passage_MTAB$p_adjusted<0.05 & abs(passage_MTAB$db)>0.15),] #58958
diff_CpG_db_hypoMTAB<-diff_CpG_dbMTAB$CpG[which((diff_CpG_dbMTAB$db)>=0.15)] # 45098
diff_CpG_db_hyperMTAB<-diff_CpG_dbMTAB$CpG[which((diff_CpG_dbMTAB$db)<=(-0.15))] # 13860
How many differential CpGs could overlap? 450K vs EPIC
print(paste("Of the ", nrow(diff_CpG_db), " CpGs differential with passage in the original organoids, ",
length(diff_CpG_db$CpG[which(diff_CpG_db$CpG%in%rownames(MTAB_organoid_beta_fetal))]), " are in the 450K data", sep=""))
## [1] "Of the 23766 CpGs differential with passage in the original organoids, 7628 are in the 450K data"
diff_CpG_db_hypo_overlap<-diff_CpG_db_hypo[which(diff_CpG_db_hypo%in%rownames(MTAB_organoid_beta_fetal))]
diff_CpG_db_hyper_overlap<-diff_CpG_db_hyper[which(diff_CpG_db_hyper%in%rownames(MTAB_organoid_beta_fetal))]
diff_CpG_db_hypoMTAB_overlap<-diff_CpG_db_hypoMTAB[which(diff_CpG_db_hypoMTAB%in%pvals_long$CpG)]
diff_CpG_db_hyperMTAB_overlap<-diff_CpG_db_hyperMTAB[which(diff_CpG_db_hyperMTAB%in%pvals_long$CpG)]
print(paste("Of the ",length(diff_CpG_db_hypo_overlap)," hypo CpGs also on the 450K ",
length(intersect(diff_CpG_db_hypoMTAB_overlap, diff_CpG_db_hypo_overlap))," are also hypo in the MTAB-4957 cohort (",
round((length(intersect(diff_CpG_db_hypoMTAB_overlap, diff_CpG_db_hypo_overlap))/length(diff_CpG_db_hypo_overlap))*100,2),"%)",sep=""))
## [1] "Of the 5098 hypo CpGs also on the 450K 3980 are also hypo in the MTAB-4957 cohort (78.07%)"
print(paste("Of the ",length(diff_CpG_db_hyper_overlap)," hyper CpGs also on the 450K ",
length(intersect(diff_CpG_db_hyperMTAB_overlap, diff_CpG_db_hyper_overlap))," are also hypo in the MTAB-4957 cohort (",
round((length(intersect(diff_CpG_db_hyperMTAB_overlap, diff_CpG_db_hyper_overlap))/length(diff_CpG_db_hyper_overlap))*100,2),"%)",sep=""))
## [1] "Of the 2530 hyper CpGs also on the 450K 845 are also hypo in the MTAB-4957 cohort (33.4%)"
### delta beta directionality plot
plt_db_direction<-merge(pvals_long[,c(3,6)], passage_MTAB, by="CpG")
plt_db_direction$sig<-"Not Significant"
plt_db_direction$sig[which(plt_db_direction$CpG%in%c(intersect(diff_CpG_db_hypoMTAB_overlap, diff_CpG_db_hypo_overlap),intersect(diff_CpG_db_hyperMTAB_overlap, diff_CpG_db_hyper_overlap)))]<-"Significant\nIn Both\nCohorts"
ggplot(plt_db_direction, aes(mean_db, db))+geom_point(aes(color=sig, alpha=sig),shape=19)+th+theme_bw()+
scale_color_manual(values=c("lightgrey", "cornflowerblue"), name="Significant\nWith Passage")+
scale_alpha_manual(values=c(0.25,1), guide=F)+
geom_hline(yintercept=c(-0.15,0.15), color="grey60")+geom_vline(xintercept=c(-0.15,0.15), color="grey60")+
ylim(-0.8,0.8)+xlim(-0.8,0.8)+xlab("Cohort 1\nPassage Delta Beta")+ylab("Cohort 2 Fetal Organoid\nPassage Delta Beta")+
stat_smooth(method="lm", se=F, color="black")
## Warning: Removed 201 rows containing non-finite values (stat_smooth).
## Warning: Removed 201 rows containing missing values (geom_point).
#ggsave(here("figs","MTAB_db_directionality_fetal.pdf"), width=5, height=3.75)
ggsave(here("figs/jpeg","MTAB_db_directionality_fetal.jpeg"), width=5, height=3.75)
## Warning: Removed 201 rows containing non-finite values (stat_smooth).
## Warning: Removed 201 rows containing missing values (geom_point).
print(paste("Correlation of delta betas between cohorts: ", round(cor(plt_db_direction$db, plt_db_direction$mean_db),2), sep=""))
## [1] "Correlation of delta betas between cohorts: 0.5"
sampleinfo_organoid_fetal_minimal<-sampleinfo_organoid_fetal[,c(16,22,21)]
sampleinfo_organoid_fetal_minimal$cohort<-"Cohort 2 Fetal Organoids"
sample_info_both<-rbind(sampleinfo_organoid_fetal_minimal,epic.organoid_minimal)
plt_hetero_MTAB<-function(CpGs, legend, axislab, title){
betas<-melt(cbind(MTAB_organoid_beta_fetal[CpGs,],organoid_beta[CpGs,]))
organoid_plt<-merge(sample_info_both, betas, by.x="Assay.Name",by.y="Var2")
p<-ggplot(organoid_plt, aes(passage.or.rescope.no_numeric,value))+
geom_line(aes(group=sample_ID),color="lightgrey")+
stat_smooth(method="lm", color="grey30", size=0.7, se=F)+th+theme_bw()+
geom_point(aes(fill=as.factor(passage.or.rescope.no_numeric)),shape=21, size=1.25)+
scale_fill_manual(values=pass_col,name="Passage\nNumber", drop=T)+
facet_grid(cohort~Var1)+
ylab("DNAm Beta")+xlab("Passage Number")+ylim(0,1)+
theme(plot.margin = margin(0.5, 0.15, 0.5, 0.15, "cm"),plot.title = element_text(size=12), legend.key.size = unit(0.4, "cm"))+
xlim(1,23)
if(missing(legend) & missing(axislab) & missing(title)){p}else{
if(legend=="N" & axislab=="N"){p + theme(legend.position = "none",axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())+ ggtitle(title)}else{
if(legend=="N" & axislab=="Y"){p + theme(legend.position = "none") + ggtitle(title)}}}}
plt_hetero_MTAB(c("cg25402228","cg09146328"))
ggsave(here("figs","Passage_differential_CpGs_MTAB4957_fetal.pdf"),width = 4.75, height = 4)
ggsave(here("figs/jpeg","Passage_differential_CpGs_MTAB4957_fetal.jpeg"), width = 4.75, height = 4)
sessionInfo()
## R version 3.5.1 (2018-07-02)
## Platform: x86_64-conda_cos6-linux-gnu (64-bit)
## Running under: Red Hat Enterprise Linux
##
## Matrix products: default
## BLAS/LAPACK: /homes/redgar/anaconda3/envs/org_pass/lib/R/lib/libRblas.so
##
## locale:
## [1] LC_CTYPE=en_GB.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_GB.UTF-8 LC_COLLATE=en_GB.UTF-8
## [5] LC_MONETARY=en_GB.UTF-8 LC_MESSAGES=en_GB.UTF-8
## [7] LC_PAPER=en_GB.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] splines stats4 parallel stats graphics grDevices utils
## [8] datasets methods base
##
## other attached packages:
## [1] IlluminaHumanMethylation450kanno.ilmn12.hg19_0.6.0
## [2] IlluminaHumanMethylation450kmanifest_0.4.0
## [3] VGAM_1.1-1
## [4] reshape2_1.4.3
## [5] scales_1.0.0
## [6] limma_3.38.3
## [7] binom_1.1-1
## [8] here_0.1
## [9] RColorBrewer_1.1-2
## [10] gridExtra_2.3
## [11] ggplot2_3.1.0
## [12] reshape_0.8.8
## [13] minfi_1.28.0
## [14] bumphunter_1.24.5
## [15] locfit_1.5-9.1
## [16] iterators_1.0.10
## [17] foreach_1.4.4
## [18] Biostrings_2.50.1
## [19] XVector_0.22.0
## [20] SummarizedExperiment_1.12.0
## [21] DelayedArray_0.8.0
## [22] BiocParallel_1.16.2
## [23] matrixStats_0.54.0
## [24] Biobase_2.42.0
## [25] GenomicRanges_1.34.0
## [26] GenomeInfoDb_1.18.1
## [27] IRanges_2.16.0
## [28] S4Vectors_0.20.1
## [29] BiocGenerics_0.28.0
##
## loaded via a namespace (and not attached):
## [1] colorspace_1.4-0 siggenes_1.56.0
## [3] mclust_5.4.2 rprojroot_1.3-2
## [5] base64_2.0 bit64_0.9-7
## [7] AnnotationDbi_1.44.0 xml2_1.2.0
## [9] codetools_0.2-16 knitr_1.21
## [11] Rsamtools_1.34.0 annotate_1.60.0
## [13] HDF5Array_1.10.1 readr_1.3.1
## [15] compiler_3.5.1 httr_1.4.0
## [17] backports_1.1.3 assertthat_0.2.0
## [19] Matrix_1.2-15 lazyeval_0.2.1
## [21] htmltools_0.3.6 prettyunits_1.0.2
## [23] tools_3.5.1 gtable_0.2.0
## [25] glue_1.3.0 GenomeInfoDbData_1.2.0
## [27] dplyr_0.8.0.1 doRNG_1.7.1
## [29] Rcpp_1.0.0 multtest_2.38.0
## [31] preprocessCore_1.44.0 nlme_3.1-137
## [33] rtracklayer_1.42.2 DelayedMatrixStats_1.4.0
## [35] xfun_0.4 stringr_1.4.0
## [37] rngtools_1.3.1 XML_3.98-1.16
## [39] beanplot_1.2 zlibbioc_1.28.0
## [41] MASS_7.3-51.1 hms_0.4.2
## [43] rhdf5_2.26.2 GEOquery_2.50.0
## [45] yaml_2.2.0 memoise_1.1.0
## [47] pkgmaker_0.27 biomaRt_2.38.0
## [49] stringi_1.2.4 RSQLite_2.1.1
## [51] highr_0.7 genefilter_1.64.0
## [53] GenomicFeatures_1.34.1 bibtex_0.4.2
## [55] rlang_0.3.1 pkgconfig_2.0.2
## [57] bitops_1.0-6 nor1mix_1.2-3
## [59] evaluate_0.12 lattice_0.20-38
## [61] purrr_0.2.5 Rhdf5lib_1.4.2
## [63] labeling_0.3 GenomicAlignments_1.18.0
## [65] bit_1.1-12 tidyselect_0.2.5
## [67] plyr_1.8.4 magrittr_1.5
## [69] R6_2.4.0 DBI_1.0.0
## [71] pillar_1.4.3 withr_2.1.2
## [73] survival_2.43-3 RCurl_1.95-4.11
## [75] tibble_2.0.1 crayon_1.3.4
## [77] rmarkdown_1.11 progress_1.2.0
## [79] grid_3.5.1 data.table_1.12.0
## [81] blob_1.1.1 digest_0.6.18
## [83] xtable_1.8-2 tidyr_0.8.2
## [85] illuminaio_0.24.0 openssl_1.1
## [87] munsell_0.5.0 registry_0.5
## [89] quadprog_1.5-5